{"title":"ELISA","description":"","products":[{"product_id":"polr2a-antibody-sc-f0023","title":"Phospho-RNA pol II CTD (Ser5) Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003ePOLR2A is a target of interest in many antibody-based workflows. Eukaryotes possess three nuclear DNA-dependent RNA polymerases (RNAPs): RNAP I, RNAP II, and RNAP III. RNAP II, responsible for synthesizing mRNA and many noncoding RNAs (ncRNAs), consists of 12 polypeptides. The largest subunit, Rpb1, harbors the enzyme's catalytic activity and a unique C-terminal domain (CTD) composed of tandem heptad repeats (consensus Tyr1-Ser2-Pro3-Thr4-Ser5-Pro6-Ser7). Depending on the literature source, POLR2A may also be discussed as Phospho-RNA pol II CTD (Ser5) and Phospho RNA polymerase II CTD repeat YSPTSPS (Ser 5).\u003c\/p\u003e\u003cp\u003eReported cellular context includes nucleus, cytoplasm, and chromosome, which can matter when signal is compared across treatments or changing cell states. Following POLR2A across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003ePOLR2A is commonly interpreted in the context of cell signaling research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans nucleus, cytoplasm, and chromosome, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between nucleus, cytoplasm, and chromosome across matched conditions\u003c\/li\u003e\n\u003cli\u003esignal-dependent shifts after ligand, inhibitor, or growth-factor perturbation\u003c\/li\u003e\n\u003cli\u003edifferences between total target abundance and site-specific regulation when modified forms are compared\u003c\/li\u003e\n\u003cli\u003eco-patterning with orthogonal markers and control conditions that clarify pathway state\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for POLR2A. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in POLR2A reflect biology rather than handling. When interpreting POLR2A, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep POLR2A trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577380381017,"sku":"F0023-20UL","price":189.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577380413785,"sku":"F0023-100UL","price":389.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577380446553,"sku":"F0023-2X100UL","price":579.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0023-IF.png?v=1773598087"},{"product_id":"calb1-antibody-sc-f0032","title":"Calbindin-D-28K Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eCALB1 is a target of interest in many antibody-based workflows. Calbindin-D-28K is a highly conserved 28kDa calcium-binding protein that belongs to a family of low molecular weight calcium-binding proteins (CaBPs) together with calmodulin, S-100, parvalbumin, troponin C, and other proteins. Calbindin-D-28K is prominently found in specific populations of neurons within the central and peripheral nervous systems. Depending on the literature source, CALB1 may also be discussed as Calbindin-D-28K and Calbindin.\u003c\/p\u003e\u003cp\u003eReported cellular context includes nucleus, cytosol, synapse, and exosome, which can matter when signal is compared across treatments or changing cell states. Following CALB1 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eCALB1 is commonly interpreted in the context of neuroscience research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans nucleus, cytosol, and synapse, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between nucleus, cytosol, and synapse across matched conditions\u003c\/li\u003e\n\u003cli\u003ecompartment-specific patterns relevant to neuronal polarity, transport, or synaptic context\u003c\/li\u003e\n\u003cli\u003eco-patterning with orthogonal markers and control conditions that clarify pathway state\u003c\/li\u003e\n\u003cli\u003etime-matched comparisons so changes reflect biology rather than handling or sampling drift\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for CALB1. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in CALB1 reflect biology rather than handling. When interpreting CALB1, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep CALB1 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577381658969,"sku":"F0032-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577381691737,"sku":"F0032-100UL","price":359.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577381724505,"sku":"F0032-2X100UL","price":539.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/f0032-IHC1.jpg?v=1773598094"},{"product_id":"bax-antibody-sc-f0037","title":"Bax Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eThe mechanisms of apoptosis contribute to understanding the pathologies associated with uncontrolled cell growth or death. Apoptosis involves two major pathways: the extrinsic or death receptor pathway and the intrinsic or mitochondrial pathway. The intrinsic pathway is regulated by the Bcl-2 (B-cell lymphoma 2) family of proteins, which can be classified based on their anti-apoptotic (e. g., Bcl-2, Bcl-x, Bcl-w, Mcl-1, and A1\/Bfl-1) or pro-apoptotic (e. g., Bax, Bak, and Bok\/Mtd) actions. Depending on the literature source, BAX may also be discussed as NT.\u003c\/p\u003e\u003cp\u003eReported cellular context includes mitochondrion outer membrane and cytoplasm, which can matter when signal is compared across treatments or changing cell states. Following BAX across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eBAX is commonly interpreted in the context of cancer, metabolism, and apoptosis research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans mitochondrion outer membrane and cytoplasm, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between mitochondrion outer membrane and cytoplasm across matched conditions\u003c\/li\u003e\n\u003cli\u003echanges associated with proliferative state, oncogenic signaling, or treatment response\u003c\/li\u003e\n\u003cli\u003eresponses linked to nutrient status, mitochondrial state, or metabolic rewiring\u003c\/li\u003e\n\u003cli\u003eseparation of survival-associated changes from stress or death-associated readouts\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for BAX. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in BAX reflect biology rather than handling. When interpreting BAX, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep BAX trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577381757273,"sku":"F0037-20UL","price":139.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577381790041,"sku":"F0037-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577381822809,"sku":"F0037-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0037-IHC1.jpg?v=1773598096"},{"product_id":"histone-h3-antibody-sc-f0058","title":"Histone H3 (di methyl Lys9) Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eHistone H3 is a target of interest in many antibody-based workflows. Histones are essential DNA-binding proteins present in the chromatin of all eukaryotic cells, known for their high conservation. They are categorized into five primary classes: H1\/H5, H2A, H2B, H3, and H4. The core of the nucleosome, the fundamental unit of chromatin, is formed by two copies of each of the H2A, H2B, H3, and H4 histones. Depending on the literature source, Histone H3 may also be discussed as Histone H3 (di methyl Lys9) and dimethyl-Histone H3 (Lys9).\u003c\/p\u003e\u003cp\u003eReported cellular context includes nucleus and chromosome, which can matter when signal is compared across treatments or changing cell states. Following Histone H3 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eHistone H3 is commonly interpreted in the context of epigenetics research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans nucleus and chromosome, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between nucleus and chromosome across matched conditions\u003c\/li\u003e\n\u003cli\u003elinks between target behavior and transcriptional or chromatin-state changes\u003c\/li\u003e\n\u003cli\u003edifferences between total target abundance and site-specific regulation when modified forms are compared\u003c\/li\u003e\n\u003cli\u003eco-patterning with orthogonal markers and control conditions that clarify pathway state\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for Histone H3. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in Histone H3 reflect biology rather than handling. When interpreting Histone H3, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep Histone H3 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577382347097,"sku":"F0058-20UL","price":159.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577382379865,"sku":"F0058-100UL","price":359.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577382412633,"sku":"F0058-2X100UL","price":539.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0058-IF.png?v=1773598105"},{"product_id":"tau-antibody-sc-f0928","title":"Tau Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eMicrotubules (MTs) are crucial for many cellular processes, such as cell division and neuronal function. Tau, a microtubule-associated protein (MAP), is mainly found in neurons and plays a key role in promoting microtubule assembly and stabilizing microtubules. It is located on chromosome 17q21, and six isoforms of tau are produced by alternative splicing in the adult human brain.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell membrane, cell projection, cytoplasm, and cytoskeleton, which can matter when signal is compared across treatments or changing cell states. Following TAU across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eTAU is commonly interpreted in the context of neuroscience research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cell membrane, cell projection, and cytoplasm, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cell membrane, cell projection, and cytoplasm across matched conditions\u003c\/li\u003e\n\u003cli\u003ecompartment-specific patterns relevant to neuronal polarity, transport, or synaptic context\u003c\/li\u003e\n\u003cli\u003eco-patterning with orthogonal markers and control conditions that clarify pathway state\u003c\/li\u003e\n\u003cli\u003etime-matched comparisons so changes reflect biology rather than handling or sampling drift\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for TAU. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in TAU reflect biology rather than handling. When interpreting TAU, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep TAU trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577572794713,"sku":"F0928-20UL","price":179.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577572827481,"sku":"F0928-100UL","price":399.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577572860249,"sku":"F0928-2X100UL","price":599.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0928-IHC1.jpg?v=1773599108"},{"product_id":"dykddddk-tag-antibody-sc-f0973","title":"DYKDDDDK Tag Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eThe DYKDDDDK Tag stands out as a protein tag widely utilized in protein purification procedures due to its ability to confer high specificity and purity to target proteins. Its distinctive feature of being easily recognized by antibodies greatly enhances its utility in applications such as western blotting and ELISA. Depending on the literature source, DYKDDDDK Tag may also be discussed as DDDDK tag and DYKDDDDK Epitope Tag.\u003c\/p\u003e\u003cp\u003eReported cellular context includes l24h1, which can matter when signal is compared across treatments or changing cell states. Following DYKDDDDK Tag across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eDYKDDDDK Tag is commonly interpreted in the context of cell signaling research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans l24h1, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003esignal enrichment within l24h1 relative to the broader cellular background\u003c\/li\u003e\n\u003cli\u003esignal-dependent shifts after ligand, inhibitor, or growth-factor perturbation\u003c\/li\u003e\n\u003cli\u003eco-patterning with orthogonal markers and control conditions that clarify pathway state\u003c\/li\u003e\n\u003cli\u003etime-matched comparisons so changes reflect biology rather than handling or sampling drift\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for DYKDDDDK Tag. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in DYKDDDDK Tag reflect biology rather than handling. When interpreting DYKDDDDK Tag, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep DYKDDDDK Tag trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577582035289,"sku":"F0973-20UL","price":139.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577582068057,"sku":"F0973-100UL","price":319.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577582100825,"sku":"F0973-2X100UL","price":479.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0973-IF.png?v=1773599147"},{"product_id":"bsg-antibody-sc-f0982","title":"CD147 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eBSG is a target of interest in many antibody-based workflows. A cluster of differentiation 147 (CD147) is a glycoprotein originally that regulates Matrix Metalloproteinase (MMP) through cell-matrix and cell-cell interaction. It is located on chromosome 19. CD147 interacts with caveolin-1, monocarboxylate transporter, CD98, and β1 integrin and promotes various processes such as cell metabolism, proliferation, migration, and invasion. Depending on the literature source, BSG may also be discussed as CD147 and Basigin\/EMMPRIN.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell membrane, cell projection, endoplasmic reticulum, and membrane, which can matter when signal is compared across treatments or changing cell states. Following BSG across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eBSG is commonly interpreted in the context of cancer, metabolism, and cell signaling research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cell membrane, cell projection, and endoplasmic reticulum, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cell membrane, cell projection, and endoplasmic reticulum across matched conditions\u003c\/li\u003e\n\u003cli\u003echanges associated with proliferative state, oncogenic signaling, or treatment response\u003c\/li\u003e\n\u003cli\u003eresponses linked to nutrient status, mitochondrial state, or metabolic rewiring\u003c\/li\u003e\n\u003cli\u003esignal-dependent shifts after ligand, inhibitor, or growth-factor perturbation\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for BSG. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in BSG reflect biology rather than handling. When interpreting BSG, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep BSG trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577583182169,"sku":"F0982-20UL","price":159.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577583214937,"sku":"F0982-100UL","price":339.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577583247705,"sku":"F0982-2X100UL","price":499.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0982-IF.png?v=1773599152"},{"product_id":"bad-antibody-sc-f1060","title":"Bad Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eMalignant transformation of normal cells can arise from aberrant gene expression that disrupts the regulation of key cellular processes such as proliferation, apoptosis, senescence, and DNA repair. Among the pathways implicated, the Bcl-2 antagonist of cell death (BAD)-mediated apoptotic pathway plays a significant role in both carcinogenesis and the cellular response to chemotherapy. Depending on the literature source, BAD may also be discussed as Bcl2-associated agonist of cell death and Bcl-2-binding component 6.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm, membrane, mitochondrion, and mitochondrion outer membrane, which can matter when signal is compared across treatments or changing cell states. Following BAD across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eBAD is commonly interpreted in the context of cancer, metabolism, and apoptosis research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cytoplasm, membrane, and mitochondrion, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cytoplasm, membrane, and mitochondrion across matched conditions\u003c\/li\u003e\n\u003cli\u003echanges associated with proliferative state, oncogenic signaling, or treatment response\u003c\/li\u003e\n\u003cli\u003eresponses linked to nutrient status, mitochondrial state, or metabolic rewiring\u003c\/li\u003e\n\u003cli\u003eseparation of survival-associated changes from stress or death-associated readouts\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for BAD. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in BAD reflect biology rather than handling. When interpreting BAD, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep BAD trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577601499481,"sku":"F1060-20UL","price":139.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577601532249,"sku":"F1060-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577601565017,"sku":"F1060-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1060-IF.png?v=1773599236"},{"product_id":"esr1-antibody-sc-f1063","title":"Estrogen Receptor α Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eESR1 is a target of interest in many antibody-based workflows. Estrogen receptor α (ERα) is a ligand-dependent transcription factor and part of the nuclear hormone receptor (NHR) superfamily. It has a globular ligand-binding domain (LBD) that facilitates hormone binding, dimerization, and interaction with coregulators. The human ERα gene is located on chromosome 6, and the full-length protein consists of 595 amino acids with a molecular size of 66 kDa. Depending on the literature source, ESR1 may also be discussed as Estrogen Receptor alpha.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell membrane, cytoplasm, golgi apparatus, and membrane, which can matter when signal is compared across treatments or changing cell states. Following ESR1 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eESR1 is commonly interpreted in the context of cancer, cardiovascular, and metabolism research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cell membrane, cytoplasm, and golgi apparatus, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cell membrane, cytoplasm, and golgi apparatus across matched conditions\u003c\/li\u003e\n\u003cli\u003echanges associated with proliferative state, oncogenic signaling, or treatment response\u003c\/li\u003e\n\u003cli\u003echanges linked to vascular, contractile, or hemodynamic cell-state cues\u003c\/li\u003e\n\u003cli\u003eresponses linked to nutrient status, mitochondrial state, or metabolic rewiring\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for ESR1. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in ESR1 reflect biology rather than handling. When interpreting ESR1, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep ESR1 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577601630553,"sku":"F1063-20UL","price":139.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577601663321,"sku":"F1063-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577601696089,"sku":"F1063-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1063-IF.png?v=1773599236"},{"product_id":"hspa8-hsc70-antibody-sc-f1064","title":"HSPA8\/HSC70 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eHSPA8\/HSC70 is a target of interest in many antibody-based workflows. The HSP70 family consists of four highly conserved proteins: HSP70, HSC70, GRP75, and GRP78. These proteins act as molecular chaperones and are essential for assembling multi-protein complexes and transporting polypeptides across cell membranes and nuclei. HSP70 and HSP90 are molecular chaperones that are expressed continuously to maintain protein balance under normal conditions and are induced during environmental stress. Depending on the literature source, HSPA8\/HSC70 may also be discussed as HSPA8\/HSC70 and Hsc70.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell membrane, cytoplasm, lysosome, and membrane, which can matter when signal is compared across treatments or changing cell states. Following HSPA8\/HSC70 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eHSPA8\/HSC70 is commonly interpreted in the context of endocrinology research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cell membrane, cytoplasm, and lysosome, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cell membrane, cytoplasm, and lysosome across matched conditions\u003c\/li\u003e\n\u003cli\u003eresponses to hormone-dependent signaling or endocrine feedback context\u003c\/li\u003e\n\u003cli\u003eco-patterning with orthogonal markers and control conditions that clarify pathway state\u003c\/li\u003e\n\u003cli\u003etime-matched comparisons so changes reflect biology rather than handling or sampling drift\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for HSPA8\/HSC70. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in HSPA8\/HSC70 reflect biology rather than handling. When interpreting HSPA8\/HSC70, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep HSPA8\/HSC70 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577601728857,"sku":"F1064-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577601761625,"sku":"F1064-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577601794393,"sku":"F1064-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1064-IF.png?v=1773599237"},{"product_id":"elavl1-antibody-sc-f1065","title":"HuR\/ELAV1 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eELAVL1 is a target of interest in many antibody-based workflows. Eukaryotic gene expression is controlled through various mechanisms, including transcription, mRNA processing, transport, localization, turnover, and translation. RNA-binding proteins (RBPs) are key players in regulating gene expression and participate in all stages of mRNA processing, from splicing to translation. One such RBP is Human antigen R (HuR), which primarily regulates mRNA transport from the nucleus to the cytoplasm, mRNA stability, and translation. Depending on the literature source, ELAVL1 may also be discussed as HuR\/ELAV1 and ELAVL1\/HuR.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm and nucleus, which can matter when signal is compared across treatments or changing cell states. Following ELAVL1 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eELAVL1 is commonly interpreted in the context of cancer and immunology research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cytoplasm and nucleus, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cytoplasm and nucleus across matched conditions\u003c\/li\u003e\n\u003cli\u003echanges associated with proliferative state, oncogenic signaling, or treatment response\u003c\/li\u003e\n\u003cli\u003econtext differences tied to immune-cell state, activation, or lineage composition\u003c\/li\u003e\n\u003cli\u003eco-patterning with orthogonal markers and control conditions that clarify pathway state\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for ELAVL1. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in ELAVL1 reflect biology rather than handling. When interpreting ELAVL1, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep ELAVL1 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577602318681,"sku":"F1065-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577602351449,"sku":"F1065-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577602384217,"sku":"F1065-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1065-IF.png?v=1773599239"},{"product_id":"ve-cadherin-antibody-sc-f1068","title":"VE-cadherin Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eVE-cadherin, also known as vascular endothelial cadherin or CD144, is a critical transmembrane protein predominantly expressed in endothelial cells, where it plays a vital role in maintaining cell-cell junctions that regulate vascular permeability and integrity. As a member of the cadherin superfamily, VE-cadherin features a unique structure composed of an extracellular domain responsible for homophilic binding to adjacent VE-cadherin molecules, a single transmembrane domain and an intracellular domain that interacts with catenins such as β-catenin and p120-catenin.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell junction, cell membrane, cytoplasm, and membrane, which can matter when signal is compared across treatments or changing cell states. Following VE-CADHERIN across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eVE-CADHERIN is commonly interpreted in the context of immunology, cardiovascular, and angiogenesis research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cell junction, cell membrane, and cytoplasm, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cell junction, cell membrane, and cytoplasm across matched conditions\u003c\/li\u003e\n\u003cli\u003econtext differences tied to immune-cell state, activation, or lineage composition\u003c\/li\u003e\n\u003cli\u003echanges linked to vascular, contractile, or hemodynamic cell-state cues\u003c\/li\u003e\n\u003cli\u003edifferences related to endothelial activation, vessel remodeling, or growth-factor exposure\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for VE-CADHERIN. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in VE-CADHERIN reflect biology rather than handling. When interpreting VE-CADHERIN, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep VE-CADHERIN trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577603137881,"sku":"F1068-20UL","price":199.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577603170649,"sku":"F1068-100UL","price":489.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577603203417,"sku":"F1068-2X100UL","price":729.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1068-wb.gif?v=1773599246"},{"product_id":"gdf15-antibody-sc-f1086","title":"GDF15 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eGrowth differentiation factor-15 (GDF15) is a member of the TGF-β superfamily, secreted by cells under stress. It functions as a metabolic regulator, signaling exclusively via the GFRAL-RET heterodimer to suppress appetite. This GDF15-GFRAL axis has sparked interest due to its role in controlling ingestive behavior. Depending on the literature source, GDF15 may also be discussed as MIC1.\u003c\/p\u003e\u003cp\u003eReported cellular context includes secreted, which can matter when signal is compared across treatments or changing cell states. Following GDF15 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eGDF15 is commonly interpreted in the context of metabolism research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans secreted, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003esignal enrichment within secreted relative to the broader cellular background\u003c\/li\u003e\n\u003cli\u003eresponses linked to nutrient status, mitochondrial state, or metabolic rewiring\u003c\/li\u003e\n\u003cli\u003eco-patterning with orthogonal markers and control conditions that clarify pathway state\u003c\/li\u003e\n\u003cli\u003etime-matched comparisons so changes reflect biology rather than handling or sampling drift\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for GDF15. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in GDF15 reflect biology rather than handling. When interpreting GDF15, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep GDF15 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577608315225,"sku":"F1086-20UL","price":169.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577608347993,"sku":"F1086-100UL","price":399.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577608380761,"sku":"F1086-2X100UL","price":599.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1086-IHC1.jpg?v=1773599273"},{"product_id":"h4-antibody-sc-f1090","title":"Acetyl-Histone H4 (Lys5) Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eAcetyl-Histone H4 (Lys5) refers to the post-translationally modified form of histone H4 in which the lysine residue at position 5 on its N-terminal tail is acetylated. Histone H4 is a core component of the nucleosome, the fundamental unit of chromatin in eukaryotic cells, and consists of a globular histone fold domain for nucleosome assembly and an N-terminal tail rich in lysine residues (including Lys5, Lys8, Lys12, and Lys16) that are targets for dynamic acetylation. Depending on the literature source, H4 may also be discussed as Acetyl-Histone H4 (Lys5) and H4\/A.\u003c\/p\u003e\u003cp\u003eReported cellular context includes chromosome, nucleosome core, and nucleus, which can matter when signal is compared across treatments or changing cell states. Following H4 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eH4 is commonly interpreted in the context of epigenetics research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans chromosome, nucleosome core, and nucleus, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between chromosome, nucleosome core, and nucleus across matched conditions\u003c\/li\u003e\n\u003cli\u003elinks between target behavior and transcriptional or chromatin-state changes\u003c\/li\u003e\n\u003cli\u003edifferences between total target abundance and site-specific regulation when modified forms are compared\u003c\/li\u003e\n\u003cli\u003eco-patterning with orthogonal markers and control conditions that clarify pathway state\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for H4. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in H4 reflect biology rather than handling. When interpreting H4, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep H4 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577609920857,"sku":"F1090-20UL","price":169.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577609953625,"sku":"F1090-100UL","price":389.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577609986393,"sku":"F1090-2X100UL","price":589.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1090-IF.png?v=1773599276"},{"product_id":"ntrk1-ntrk2-ntrk3-antibody-sc-f1138","title":"Pan Trk Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003ePan Trk is a target of interest in many antibody-based workflows. The NTRK gene family consists of three genes (NTRK1, NTRK2, NTRK3), which produce proteins known as neurotrophic tyrosine receptor kinases (Trk-A, Trk-B, and Trk-C). These receptors are highly expressed in neural tissue and play crucial roles in neuronal development, proliferation, synaptic plasticity, and cognition. Each receptor prefers a specific ligand: Trk-A binds to nerve growth factor, Trk-B to brain-derived neurotrophic factor and neurotrophin-4, and Trk-C to neurotrophin-3. Depending on the literature source, Pan Trk may also be discussed as Pan Trk and TRKA.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell membrane and endosome, which can matter when signal is compared across treatments or changing cell states. Following Pan Trk across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state. In practice, this target is often considered at the family or isoform-group level, so experimental interpretation benefits from matched controls and clear comparison logic.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003ePan Trk is commonly interpreted in the context of cancer, neuroscience, and developmental biology research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cell membrane and endosome, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cell membrane and endosome across matched conditions\u003c\/li\u003e\n\u003cli\u003echanges associated with proliferative state, oncogenic signaling, or treatment response\u003c\/li\u003e\n\u003cli\u003ecompartment-specific patterns relevant to neuronal polarity, transport, or synaptic context\u003c\/li\u003e\n\u003cli\u003estage-dependent patterns during differentiation, morphogenesis, or lineage commitment\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for Pan Trk. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in Pan Trk reflect biology rather than handling. When interpreting Pan Trk, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep Pan Trk trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577624109401,"sku":"F1138-20UL","price":169.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577624142169,"sku":"F1138-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577624174937,"sku":"F1138-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1138-IF.png?v=1773599334"},{"product_id":"vcam1-antibody-sc-f1145","title":"VCAM1 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eVCAM1 is a 90-kDa glycoprotein that belongs to the immunoglobulin superfamily. It acts as an adhesion molecule expressed on activated endothelial surfaces, which helps in the adhesion and movement of leukocytes across epithelial barriers, thus initiating inflammatory responses. It plays a vital role in the engraftment of hematopoietic stem cells during transplantation.\u003c\/p\u003e\u003cp\u003eReported cellular context includes membrane, which can matter when signal is compared across treatments or changing cell states. Following VCAM1 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eVCAM1 is commonly interpreted in the context of cancer, immunology, and cardiovascular research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans membrane, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003esignal enrichment within membrane relative to the broader cellular background\u003c\/li\u003e\n\u003cli\u003echanges associated with proliferative state, oncogenic signaling, or treatment response\u003c\/li\u003e\n\u003cli\u003econtext differences tied to immune-cell state, activation, or lineage composition\u003c\/li\u003e\n\u003cli\u003echanges linked to vascular, contractile, or hemodynamic cell-state cues\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for VCAM1. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in VCAM1 reflect biology rather than handling. When interpreting VCAM1, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep VCAM1 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577627844953,"sku":"F1145-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577627877721,"sku":"F1145-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577627910489,"sku":"F1145-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1145-IF.png?v=1773599347"},{"product_id":"ape-antibody-sc-f1522","title":"APE Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eAPE (apurinic\/apyrimidinic endonuclease), (also known as APE1) is a multifunctional enzyme essential for maintaining genomic stability. It primarily functions in the base excision repair (BER) pathway by cleaving DNA at abasic sites, a critical step in repairing damaged DNA. APE1 also acts as a redox regulator of transcription factors and participates in RNA metabolism and gene regulation, such as transcriptional repression via interaction with negative calcium-response elements (nCaRE). Depending on the literature source, APE may also be discussed as APE1 and Ref-1.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm, endoplasmic reticulum, mitochondrion, and nucleus, which can matter when signal is compared across treatments or changing cell states. Following APE across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eAPE is commonly interpreted in the context of metabolism and oxidative stress research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cytoplasm, endoplasmic reticulum, and mitochondrion, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cytoplasm, endoplasmic reticulum, and mitochondrion across matched conditions\u003c\/li\u003e\n\u003cli\u003eresponses linked to nutrient status, mitochondrial state, or metabolic rewiring\u003c\/li\u003e\n\u003cli\u003eredox-associated shifts that may alter abundance, localization, or pathway coupling\u003c\/li\u003e\n\u003cli\u003eco-patterning with orthogonal markers and control conditions that clarify pathway state\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for APE. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in APE reflect biology rather than handling. When interpreting APE, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep APE trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577769337177,"sku":"F1522-20UL","price":159.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577769369945,"sku":"F1522-100UL","price":339.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577769402713,"sku":"F1522-2X100UL","price":499.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1522-IF.png?v=1773599843"},{"product_id":"pdgfr-beta-antibody-sc-f1540","title":"PDGFR α\/β Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003ePdgfr Α\/BETA is a target of interest in many antibody-based workflows. The platelet-derived growth factor receptor (PDGFR) family consists of receptor tyrosine kinases that mediate cellular communication by binding to growth factors at the plasma membrane. This binding activates migration, proliferation, survival, and differentiation. The family includes two main receptors, PDGFRα and PDGFRβ, which can form homodimers (PDGFRαα and PDGFRββ) or heterodimers (PDGFRα\/β) through the dimerization of A-, B-, C-, and D-polypeptide chains. Depending on the literature source, Pdgfr Α\/BETA may also be discussed as PDGFR alpha\/beta.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell membrane, cytoplasmic vesicle, and lysosome, which can matter when signal is compared across treatments or changing cell states. Following Pdgfr Α\/BETA across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state. In practice, this target is often considered at the family or isoform-group level, so experimental interpretation benefits from matched controls and clear comparison logic.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003ePdgfr Α\/BETA is commonly interpreted in the context of cancer, stem cell biology, and cell signaling research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cell membrane, cytoplasmic vesicle, and lysosome, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cell membrane, cytoplasmic vesicle, and lysosome across matched conditions\u003c\/li\u003e\n\u003cli\u003echanges associated with proliferative state, oncogenic signaling, or treatment response\u003c\/li\u003e\n\u003cli\u003estate transitions between self-renewal, priming, and differentiation\u003c\/li\u003e\n\u003cli\u003esignal-dependent shifts after ligand, inhibitor, or growth-factor perturbation\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for Pdgfr Α\/BETA. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in Pdgfr Α\/BETA reflect biology rather than handling. When interpreting Pdgfr Α\/BETA, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep Pdgfr Α\/BETA trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577770647897,"sku":"F1540-20UL","price":199.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577770680665,"sku":"F1540-100UL","price":489.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577770713433,"sku":"F1540-2X100UL","price":729.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1540-IF.png?v=1773599848"},{"product_id":"rho-antibody-sc-f1609","title":"Rhodopsin Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eRhodopsin is a G-protein-coupled receptor (GPCR) critical for scotopic (low-light) vision in vertebrates. It consists of a polypeptide chain bound to the chromophore 11-cis-retinal, which is highly stable in the dark but undergoes efficient isomerization upon photon absorption. This structural change activates rhodopsin and its associated G-protein, transducin, facilitating visual signal transduction. Depending on the literature source, RHO may also be discussed as Rhodopsin and Opsin.\u003c\/p\u003e\u003cp\u003eReported cellular context includes membrane, cell membrane, cell projection, and cilium, which can matter when signal is compared across treatments or changing cell states. Following RHO across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eRHO is commonly interpreted in the context of neuroscience and cell signaling research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans membrane, cell membrane, and cell projection, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between membrane, cell membrane, and cell projection across matched conditions\u003c\/li\u003e\n\u003cli\u003ecompartment-specific patterns relevant to neuronal polarity, transport, or synaptic context\u003c\/li\u003e\n\u003cli\u003esignal-dependent shifts after ligand, inhibitor, or growth-factor perturbation\u003c\/li\u003e\n\u003cli\u003eco-patterning with orthogonal markers and control conditions that clarify pathway state\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for RHO. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in RHO reflect biology rather than handling. When interpreting RHO, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep RHO trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577792700761,"sku":"F1609-20UL","price":169.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577792733529,"sku":"F1609-100UL","price":379.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577792766297,"sku":"F1609-2X100UL","price":569.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/f1609-IHC1.jpg?v=1773599933"},{"product_id":"pdha1-antibody-sc-f1658","title":"Phospho-PDHA1 (Ser293) Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eThe Pyruvate Dehydrogenase Complex (PDC) catalyzes the irreversible conversion of pyruvate to acetyl-CoA, linking glycolysis to the citric acid cycle. The PDHA1 subunit, a component of the E1 enzyme, is a heterotetramer composed of two alpha (PDHA1) and two beta (PDHB) subunits. PDHA1 contains the active site for the decarboxylation of pyruvate and is critical for PDC function. Depending on the literature source, PDHA1 may also be discussed as Phospho-PDHA1 (Ser293) and Phospho PDHA1 (Ser 293).\u003c\/p\u003e\u003cp\u003eReported cellular context includes mitochondrion, which can matter when signal is compared across treatments or changing cell states. Following PDHA1 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003ePDHA1 is commonly interpreted in the context of metabolism and cell signaling research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans mitochondrion, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003esignal enrichment within mitochondrion relative to the broader cellular background\u003c\/li\u003e\n\u003cli\u003eresponses linked to nutrient status, mitochondrial state, or metabolic rewiring\u003c\/li\u003e\n\u003cli\u003esignal-dependent shifts after ligand, inhibitor, or growth-factor perturbation\u003c\/li\u003e\n\u003cli\u003edifferences between total target abundance and site-specific regulation when modified forms are compared\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for PDHA1. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in PDHA1 reflect biology rather than handling. When interpreting PDHA1, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep PDHA1 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577811935577,"sku":"F1658-20UL","price":189.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577811968345,"sku":"F1658-100UL","price":389.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577812001113,"sku":"F1658-2X100UL","price":579.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1658-IHC1.jpg?v=1773599994"},{"product_id":"rip3-antibody-sc-f1682","title":"Phospho-RIP3 (Ser232) Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eThe receptor-interacting protein (RIP) family of serine\/threonine kinases-including RIP1, RIP2, RIP3, and RIP4-plays a crucial role in modulating cellular stress responses. These kinases are involved in initiating pro-survival and inflammatory signaling, primarily through NF-κB activation, as well as in promoting cell death pathways such as apoptosis. Depending on the literature source, RIP3 may also be discussed as Phospho-RIP3 (Ser232) and Ripk3.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm and nucleus, which can matter when signal is compared across treatments or changing cell states. Following RIP3 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eRIP3 is commonly interpreted in the context of inflammation, apoptosis, and cell signaling research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cytoplasm and nucleus, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cytoplasm and nucleus across matched conditions\u003c\/li\u003e\n\u003cli\u003eresponses associated with cytokine exposure, inflammatory tone, or tissue stress\u003c\/li\u003e\n\u003cli\u003eseparation of survival-associated changes from stress or death-associated readouts\u003c\/li\u003e\n\u003cli\u003esignal-dependent shifts after ligand, inhibitor, or growth-factor perturbation\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for RIP3. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in RIP3 reflect biology rather than handling. When interpreting RIP3, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep RIP3 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577817571673,"sku":"F1682-20UL","price":189.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577817604441,"sku":"F1682-100UL","price":389.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577817637209,"sku":"F1682-2X100UL","price":579.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1682-wb.gif?v=1773600018"},{"product_id":"pi3-kinase-p85alpha-antibody-sc-f1720","title":"PI3 Kinase p85α Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003ePI3 Kinase P85ALPHA is a target of interest in many antibody-based workflows. Phosphoinositide 3-kinase (PI3K) p85α is a regulatory subunit essential for controlling the PI3K signaling pathway, pivotal in regulating cell growth, survival, and metabolism. p85α interacts with the catalytic subunit p110 of PI3K, inhibiting p110's activity in its basal state and stabilizing it for controlled activation in response to cellular signals. This interaction is primarily mediated through the N-terminal SH2 domains of p85α, which bind to phosphorylated tyrosine residues on activated receptors. Depending on the literature source, PI3 Kinase P85ALPHA may also be discussed as PI3K p85alpha.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell membrane, cell junction, cytoplasm, and cytosol, which can matter when signal is compared across treatments or changing cell states. Following PI3 Kinase P85ALPHA across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003ePI3 Kinase P85ALPHA is commonly interpreted in the context of cancer, metabolism, and cell signaling research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cell membrane, cell junction, and cytoplasm, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cell membrane, cell junction, and cytoplasm across matched conditions\u003c\/li\u003e\n\u003cli\u003echanges associated with proliferative state, oncogenic signaling, or treatment response\u003c\/li\u003e\n\u003cli\u003eresponses linked to nutrient status, mitochondrial state, or metabolic rewiring\u003c\/li\u003e\n\u003cli\u003esignal-dependent shifts after ligand, inhibitor, or growth-factor perturbation\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for PI3 Kinase P85ALPHA. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in PI3 Kinase P85ALPHA reflect biology rather than handling. When interpreting PI3 Kinase P85ALPHA, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep PI3 Kinase P85ALPHA trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577831596377,"sku":"F1720-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577831629145,"sku":"F1720-100UL","price":319.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577831661913,"sku":"F1720-2X100UL","price":479.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1720-IHC1.jpg?v=1773600070"},{"product_id":"tps2-antibody-sc-f1781","title":"Mast Cell Tryptase Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eTPS2 is a target of interest in many antibody-based workflows. Mast cell tryptase is a highly conserved, tetrameric serine protease predominantly produced and stored in large quantities within the secretory granules of mast cells, which play a central role in allergic reactions, inflammation, and tissue defense. It exists mainly as a stable tetramer formed by four identical subunits (each ~30-36 kDa), with each monomer encompassing a classic serine protease catalytic triad (serine, histidine, aspartate), multiple cysteine-rich motifs forming disulfide bonds for structural stability, and distinct heparin-binding sites that stabilize the active enzyme and localize it to the acidic, heparin-rich granule core. Depending on the literature source, TPS2 may also be discussed as Mast Cell Tryptase and TPS1.\u003c\/p\u003e\u003cp\u003eReported cellular context includes secreted, which can matter when signal is compared across treatments or changing cell states. Following TPS2 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state. In practice, this target is often considered at the family or isoform-group level, so experimental interpretation benefits from matched controls and clear comparison logic.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eTPS2 is commonly interpreted in the context of immunology and inflammation research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans secreted, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003esignal enrichment within secreted relative to the broader cellular background\u003c\/li\u003e\n\u003cli\u003econtext differences tied to immune-cell state, activation, or lineage composition\u003c\/li\u003e\n\u003cli\u003eresponses associated with cytokine exposure, inflammatory tone, or tissue stress\u003c\/li\u003e\n\u003cli\u003eco-patterning with orthogonal markers and control conditions that clarify pathway state\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for TPS2. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in TPS2 reflect biology rather than handling. When interpreting TPS2, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep TPS2 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577831694681,"sku":"F1781-20UL","price":199.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577831727449,"sku":"F1781-100UL","price":489.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577831760217,"sku":"F1781-2X100UL","price":729.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1781-IHC1.jpg?v=1773600071"},{"product_id":"npm1-antibody-sc-f1908","title":"NPM1 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eNucleophosmin (NPM1), B23, is an abundant nucleolar protein involved in multiple cellular processes such as ribosome biogenesis, mRNA processing, chromatin remodeling, and maintaining genomic stability. NPM1 is involved in DNA repair processes, including homologous recombination (HR) and base excision repair (BER). It gets phosphorylated and directed to sites of DNA damage, where it interacts with repair proteins like γH2AX and BRCA1 to aid in fixing double-strand breaks. Depending on the literature source, NPM1 may also be discussed as Numatrin and NO38.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm, cytoskeleton, and nucleus, which can matter when signal is compared across treatments or changing cell states. Following NPM1 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state. In practice, this target is often considered at the family or isoform-group level, so experimental interpretation benefits from matched controls and clear comparison logic.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eNPM1 is commonly interpreted in the context of cancer, dna damage \/ repair, and epigenetics research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cytoplasm, cytoskeleton, and nucleus, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cytoplasm, cytoskeleton, and nucleus across matched conditions\u003c\/li\u003e\n\u003cli\u003echanges associated with proliferative state, oncogenic signaling, or treatment response\u003c\/li\u003e\n\u003cli\u003estress-induced changes after checkpoint activation or genotoxic challenge\u003c\/li\u003e\n\u003cli\u003elinks between target behavior and transcriptional or chromatin-state changes\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for NPM1. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in NPM1 reflect biology rather than handling. When interpreting NPM1, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep NPM1 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577831989593,"sku":"F1908-20UL","price":179.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577832022361,"sku":"F1908-100UL","price":399.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577832055129,"sku":"F1908-2X100UL","price":599.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1908-IHC1.jpg?v=1773600076"},{"product_id":"histone-h3-antibody-sc-f2229","title":"Phospho-Histone H3 (Ser10\/Thr11) Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eHistone H3 (phospho Ser 10 + Thr 11) is closely associated with transcriptionally active loci, playing a crucial role in gene regulation and chromatin dynamics. H3S10 phosphorylation promotes chromatin condensation during mitosis and also marks areas of active transcription, with its dual function in cell cycle progression and gene activation. Depending on the literature source, Histone H3 may also be discussed as Phospho-Histone H3 (Ser10\/Thr11) and Phospho Histone H3 (Ser 10 + Thr 11).\u003c\/p\u003e\u003cp\u003eReported cellular context includes chromosome, nucleosome core, and nucleus, which can matter when signal is compared across treatments or changing cell states. Following Histone H3 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eHistone H3 is commonly interpreted in the context of cell cycle and epigenetics research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans chromosome, nucleosome core, and nucleus, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between chromosome, nucleosome core, and nucleus across matched conditions\u003c\/li\u003e\n\u003cli\u003ecell-cycle linked differences in abundance, timing, or compartmental enrichment\u003c\/li\u003e\n\u003cli\u003elinks between target behavior and transcriptional or chromatin-state changes\u003c\/li\u003e\n\u003cli\u003edifferences between total target abundance and site-specific regulation when modified forms are compared\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for Histone H3. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in Histone H3 reflect biology rather than handling. When interpreting Histone H3, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep Histone H3 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577900343641,"sku":"F2229-20UL","price":159.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577900376409,"sku":"F2229-100UL","price":359.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577900409177,"sku":"F2229-2X100UL","price":539.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F2229-IF.png?v=1773600290"},{"product_id":"rassf1a-antibody-sc-f2337","title":"RASSF1a Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eRASSF1A (Ras association domain family 1 isoform A) is a tumor suppressor protein frequently inactivated in human cancers, primarily through epigenetic silencing via promoter methylation. RASSF1A contains a Ras association (RA) domain and a cysteine-rich domain (CRD), which enable interactions with Ras proteins and other signalling molecules.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm, cytoskeleton, microtubule, and nucleus, which can matter when signal is compared across treatments or changing cell states. Following RASSF1A across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eRASSF1A is commonly interpreted in the context of cancer, cell cycle, and apoptosis research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cytoplasm, cytoskeleton, and microtubule, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cytoplasm, cytoskeleton, and microtubule across matched conditions\u003c\/li\u003e\n\u003cli\u003echanges associated with proliferative state, oncogenic signaling, or treatment response\u003c\/li\u003e\n\u003cli\u003ecell-cycle linked differences in abundance, timing, or compartmental enrichment\u003c\/li\u003e\n\u003cli\u003eseparation of survival-associated changes from stress or death-associated readouts\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for RASSF1A. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in RASSF1A reflect biology rather than handling. When interpreting RASSF1A, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep RASSF1A trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577908830553,"sku":"F2337-20UL","price":199.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577908863321,"sku":"F2337-100UL","price":489.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577908896089,"sku":"F2337-2X100UL","price":729.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F2337-IF.png?v=1773600308"},{"product_id":"rpa32-rpa2-antibody-sc-f2375","title":"Phospho-RPA32\/RPA2 (Thr21) Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003ePhospho-RPA32\/RPA2 (Thr21) is a target of interest in many antibody-based workflows. RPA32, also known as RPA2, is a vital subunit of the replication protein A (RPA) complex, which binds to single-stranded DNA (ssDNA) during DNA replication and repair. Phosphorylation at threonine 21 (Thr 21) occurs in response to DNA damage and is crucial for effective DNA repair, especially in homologous recombination (HR), as it enhances RPA's binding affinity for ssDNA and facilitates the recruitment of Rad51, a key player in HR that promotes genomic stability. Depending on the literature source, Phospho-RPA32\/RPA2 (Thr21) may also be discussed as Phospho-RPA32\/RPA2 (Thr21).\u003c\/p\u003e\u003cp\u003eReported cellular context includes nucleus, which can matter when signal is compared across treatments or changing cell states. Following Phospho-RPA32\/RPA2 (Thr21) across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003ePhospho-RPA32\/RPA2 (Thr21) is commonly interpreted in the context of dna damage \/ repair and cell cycle research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans nucleus, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003esignal enrichment within nucleus relative to the broader cellular background\u003c\/li\u003e\n\u003cli\u003estress-induced changes after checkpoint activation or genotoxic challenge\u003c\/li\u003e\n\u003cli\u003ecell-cycle linked differences in abundance, timing, or compartmental enrichment\u003c\/li\u003e\n\u003cli\u003edifferences between total target abundance and site-specific regulation when modified forms are compared\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for Phospho-RPA32\/RPA2 (Thr21). This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in Phospho-RPA32\/RPA2 (Thr21) reflect biology rather than handling. When interpreting Phospho-RPA32\/RPA2 (Thr21), it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep Phospho-RPA32\/RPA2 (Thr21) trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577927508313,"sku":"F2375-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577927541081,"sku":"F2375-100UL","price":359.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577927573849,"sku":"F2375-2X100UL","price":539.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F2375-wb.gif?v=1773600351"},{"product_id":"tau-antibody-sc-f2389","title":"Phospho-Tau (Thr231) Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eTau is a microtubule-associated protein (MAP) primarily expressed in neurons, where it stabilizes microtubules and regulates axonal transport. Tau’s function is tightly controlled by post-translational modifications, particularly phosphorylation. Phosphorylation at threonine 231 (Thr231) is critical for tau’s functional regulation and pathological role in neurodegenerative diseases. Depending on the literature source, TAU may also be discussed as Phospho-Tau (Thr231) and Tau (phospho T231).\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell membrane, cell projection, cytoplasm, and cytoskeleton, which can matter when signal is compared across treatments or changing cell states. Following TAU across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eTAU is commonly interpreted in the context of neuroscience and apoptosis research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cell membrane, cell projection, and cytoplasm, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cell membrane, cell projection, and cytoplasm across matched conditions\u003c\/li\u003e\n\u003cli\u003ecompartment-specific patterns relevant to neuronal polarity, transport, or synaptic context\u003c\/li\u003e\n\u003cli\u003eseparation of survival-associated changes from stress or death-associated readouts\u003c\/li\u003e\n\u003cli\u003edifferences between total target abundance and site-specific regulation when modified forms are compared\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for TAU. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in TAU reflect biology rather than handling. When interpreting TAU, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep TAU trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577931243865,"sku":"F2389-20UL","price":95.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577931276633,"sku":"F2389-100UL","price":349.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577931309401,"sku":"F2389-2X100UL","price":559.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F2389-wb.gif?v=1773600361"},{"product_id":"histone-h3-antibody-sc-f2401","title":"Histone H3 (acetyl Lys56) Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eHistone H3 (acetyl Lys 56) (H3K56ac) is a significant epigenetic modification that plays a crucial role in chromatin dynamics and gene regulation. This specific acetylation occurs on the histone H3 protein, marking newly synthesized histones during DNA replication and facilitating nucleosome assembly. H3K56ac is catalyzed by the acetyltransferase Rtt109 and is essential for the proper organization of chromatin, as it enhances the binding affinity of histone chaperones like CAF-1 and Rtt106, which are involved in depositing histones onto replicating DNA. Depending on the literature source, Histone H3 may also be discussed as Histone H3 (acetyl Lys56) and Acetyl-Histone H3 (Lys56).\u003c\/p\u003e\u003cp\u003eReported cellular context includes chromosome, nucleosome core, and nucleus, which can matter when signal is compared across treatments or changing cell states. Following Histone H3 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eHistone H3 is commonly interpreted in the context of cancer, dna damage \/ repair, and epigenetics research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans chromosome, nucleosome core, and nucleus, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between chromosome, nucleosome core, and nucleus across matched conditions\u003c\/li\u003e\n\u003cli\u003echanges associated with proliferative state, oncogenic signaling, or treatment response\u003c\/li\u003e\n\u003cli\u003estress-induced changes after checkpoint activation or genotoxic challenge\u003c\/li\u003e\n\u003cli\u003elinks between target behavior and transcriptional or chromatin-state changes\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for Histone H3. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in Histone H3 reflect biology rather than handling. When interpreting Histone H3, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep Histone H3 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577934586201,"sku":"F2401-20UL","price":169.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577934618969,"sku":"F2401-100UL","price":389.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577934651737,"sku":"F2401-2X100UL","price":579.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F2401-IF.png?v=1773600369"},{"product_id":"protein-casp-antibody-sc-f2405","title":"Protein CASP Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eProtein CASP, also known as CUX1 (Cut-like homeobox 1) is a transcription factor that plays a complex and context-dependent role in cellular functions, development, and disease, with multiple isoforms, including the p110 and p75 variants, produced through alternative splicing and proteolytic processing. These isoforms play distinct roles in regulating gene expression, cell differentiation, proliferation, migration, and invasion.\u003c\/p\u003e\u003cp\u003eReported cellular context includes golgi apparatus and membrane, which can matter when signal is compared across treatments or changing cell states. Following Protein CASP across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eProtein CASP is commonly interpreted in the context of cancer, developmental biology, and apoptosis research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans golgi apparatus and membrane, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between golgi apparatus and membrane across matched conditions\u003c\/li\u003e\n\u003cli\u003echanges associated with proliferative state, oncogenic signaling, or treatment response\u003c\/li\u003e\n\u003cli\u003estage-dependent patterns during differentiation, morphogenesis, or lineage commitment\u003c\/li\u003e\n\u003cli\u003eseparation of survival-associated changes from stress or death-associated readouts\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for Protein CASP. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in Protein CASP reflect biology rather than handling. When interpreting Protein CASP, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep Protein CASP trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577935896921,"sku":"F2405-20UL","price":199.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577935929689,"sku":"F2405-100UL","price":489.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577935962457,"sku":"F2405-2X100UL","price":729.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F2405-IF.png?v=1773600372"},{"product_id":"gamma-actin-antibody-sc-f2446","title":"γ Actin Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eGamma Actin is a target of interest in many antibody-based workflows. γ-Actin (ACTG1) is one of the three major isoforms of actin, a highly conserved protein crucial for various cellular processes, particularly in non-muscle cells. It plays a vital role in maintaining the cytoskeletal structure, facilitating cell motility, and participating in signalling pathways. Structurally, γ-actin is a globular protein that polymerizes to form filamentous actin (F-actin), contributing to the formation of microfilaments essential for cell shape and function.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm and cytoskeleton, which can matter when signal is compared across treatments or changing cell states. Following Gamma Actin across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eGamma Actin is commonly interpreted in the context of immunology research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cytoplasm and cytoskeleton, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cytoplasm and cytoskeleton across matched conditions\u003c\/li\u003e\n\u003cli\u003econtext differences tied to immune-cell state, activation, or lineage composition\u003c\/li\u003e\n\u003cli\u003eco-patterning with orthogonal markers and control conditions that clarify pathway state\u003c\/li\u003e\n\u003cli\u003etime-matched comparisons so changes reflect biology rather than handling or sampling drift\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for Gamma Actin. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in Gamma Actin reflect biology rather than handling. When interpreting Gamma Actin, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep Gamma Actin trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577945825625,"sku":"F2446-20UL","price":199.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577945858393,"sku":"F2446-100UL","price":489.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577945891161,"sku":"F2446-2X100UL","price":729.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F2446-IF.png?v=1773600409"},{"product_id":"angiotensin-converting-enzyme-1-antibody-sc-f2456","title":"Angiotensin Converting Enzyme 1 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eAngiotensin Converting Enzyme 1 is a target of interest in many antibody-based workflows. Angiotensin-converting enzyme 1 (ACE1) is crucial in the renin-angiotensin system (RAS), which regulates blood pressure, fluid balance, and cardiovascular health. ACE1 catalyzes the conversion of angiotensin I, an inactive peptide, into angiotensin II, a potent vasoconstrictor that raises blood pressure and promotes inflammation and thrombosis.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell membrane, cytoplasm, membrane, and secreted, which can matter when signal is compared across treatments or changing cell states. Following Angiotensin Converting Enzyme 1 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eAngiotensin Converting Enzyme 1 is commonly interpreted in the context of immunology, cardiovascular, and cell signaling research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cell membrane, cytoplasm, and membrane, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cell membrane, cytoplasm, and membrane across matched conditions\u003c\/li\u003e\n\u003cli\u003econtext differences tied to immune-cell state, activation, or lineage composition\u003c\/li\u003e\n\u003cli\u003echanges linked to vascular, contractile, or hemodynamic cell-state cues\u003c\/li\u003e\n\u003cli\u003esignal-dependent shifts after ligand, inhibitor, or growth-factor perturbation\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for Angiotensin Converting Enzyme 1. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in Angiotensin Converting Enzyme 1 reflect biology rather than handling. When interpreting Angiotensin Converting Enzyme 1, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep Angiotensin Converting Enzyme 1 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577950806361,"sku":"F2456-20UL","price":199.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577950839129,"sku":"F2456-100UL","price":489.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577950871897,"sku":"F2456-2X100UL","price":729.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F2456-wb.gif?v=1773600417"},{"product_id":"ca199-antibody-sc-f2466","title":"CA19-9 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eCA199 is a target of interest in many antibody-based workflows. CA19-9 (Carbohydrate antigen 19-9), also known as Sialyl Lewis A (sLeᵃ), is a sialylated Lewis blood group antigen, a tetrasaccharide glycan epitope composed of sialic acid, galactose, N-acetylglucosamine, and fucose, biosynthesized via the Lewis blood group pathway and requiring a functional Lewis antigen for its formation. CA19-9 is expressed on glycoproteins and glycolipids of epithelial cell membranes, particularly in the pancreas, biliary tract, stomach, and colon, and can be shed into the bloodstream. Depending on the literature source, CA199 may also be discussed as CA19-9 and CA19.9.\u003c\/p\u003e\u003cp\u003eReported cellular context includes c17a13, which can matter when signal is compared across treatments or changing cell states. Following CA199 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eCA199 is commonly interpreted in the context of cancer, immunology, and metabolism research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans c17a13, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003esignal enrichment within c17a13 relative to the broader cellular background\u003c\/li\u003e\n\u003cli\u003echanges associated with proliferative state, oncogenic signaling, or treatment response\u003c\/li\u003e\n\u003cli\u003econtext differences tied to immune-cell state, activation, or lineage composition\u003c\/li\u003e\n\u003cli\u003eresponses linked to nutrient status, mitochondrial state, or metabolic rewiring\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for CA199. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in CA199 reflect biology rather than handling. When interpreting CA199, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep CA199 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577953001817,"sku":"F2466-20UL","price":199.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577953034585,"sku":"F2466-100UL","price":489.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577953067353,"sku":"F2466-2X100UL","price":729.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F2466-IHC1.jpg?v=1773600430"},{"product_id":"hsp90alpha-antibody-sc-f2703","title":"HSP90α Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eHSP90ALPHA is a target of interest in many antibody-based workflows. HSP90 (Heat shock protein 90) is a highly conserved and abundant molecular chaperone essential for protein homeostasis in eukaryotic cells, where it facilitates the maturation and stabilization of key client proteins such as kinases, transcription factors, and steroid hormone receptors. Structurally, HSP90 functions as a homodimer, with each monomer comprising an N-terminal ATP-binding domain, a middle domain involved in ATP hydrolysis and client interaction, and a C-terminal domain responsible for dimerization and co-chaperone binding through the MEEVD motif. Depending on the literature source, HSP90ALPHA may also be discussed as HSP90AA1 and HSP90A.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell membrane, cytoplasm, membrane, and mitochondrion, which can matter when signal is compared across treatments or changing cell states. Following HSP90ALPHA across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eHSP90ALPHA is commonly interpreted in the context of endocrinology and cell signaling research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cell membrane, cytoplasm, and membrane, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cell membrane, cytoplasm, and membrane across matched conditions\u003c\/li\u003e\n\u003cli\u003eresponses to hormone-dependent signaling or endocrine feedback context\u003c\/li\u003e\n\u003cli\u003esignal-dependent shifts after ligand, inhibitor, or growth-factor perturbation\u003c\/li\u003e\n\u003cli\u003eco-patterning with orthogonal markers and control conditions that clarify pathway state\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for HSP90ALPHA. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in HSP90ALPHA reflect biology rather than handling. When interpreting HSP90ALPHA, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep HSP90ALPHA trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577967419737,"sku":"F2703-20UL","price":95.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577967452505,"sku":"F2703-100UL","price":289.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577967485273,"sku":"F2703-2X100UL","price":459.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F2703-IF.png?v=1773600633"},{"product_id":"pkm2-antibody-sc-f2704","title":"PKM2 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003ePKM2 (Pyruvate Kinase M2) is a versatile glycolytic enzyme encoded by the PKM gene, primarily expressed in cancer cells, embryonic tissues, and proliferating cells. It catalyzes the final step of glycolysis, converting phosphoenolpyruvate (PEP) to pyruvate, and exists in two forms: a tetrameric, high-activity form that drives glycolysis and a dimeric, low-activity form that promotes aerobic glycolysis (Warburg effect), a hallmark of cancer metabolism.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm and nucleus, which can matter when signal is compared across treatments or changing cell states. Following PKM2 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003ePKM2 is commonly interpreted in the context of cancer, metabolism, and developmental biology research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cytoplasm and nucleus, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cytoplasm and nucleus across matched conditions\u003c\/li\u003e\n\u003cli\u003echanges associated with proliferative state, oncogenic signaling, or treatment response\u003c\/li\u003e\n\u003cli\u003eresponses linked to nutrient status, mitochondrial state, or metabolic rewiring\u003c\/li\u003e\n\u003cli\u003estage-dependent patterns during differentiation, morphogenesis, or lineage commitment\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for PKM2. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in PKM2 reflect biology rather than handling. When interpreting PKM2, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep PKM2 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577967518041,"sku":"F2704-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577967550809,"sku":"F2704-100UL","price":359.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577967583577,"sku":"F2704-2X100UL","price":539.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F2704-IF.png?v=1773600635"},{"product_id":"vgr-1-antibody-sc-f2722","title":"BMP-6 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eVGR-1 is a target of interest in many antibody-based workflows. BMP-6 (Bone Morphogenetic Protein-6) is a member of the TGF-β superfamily, produced as an inactive pre-pro-polypeptide comprising an N-terminal signal peptide, a pro-domain, and a C-terminal mature domain containing seven cysteines-six forming intramolecular disulfide bonds and one mediating covalent dimerization to generate the active ligand. It is expressed in multiple embryonic and adult tissues, including developing limb buds, bone, cartilage, ovaries, liver, and the central nervous system. Depending on the literature source, VGR-1 may also be discussed as BMP-6 and Bone morphogenetic protein 6.\u003c\/p\u003e\u003cp\u003eReported cellular context includes secreted, which can matter when signal is compared across treatments or changing cell states. Following VGR-1 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eVGR-1 is commonly interpreted in the context of developmental biology research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans secreted, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003esignal enrichment within secreted relative to the broader cellular background\u003c\/li\u003e\n\u003cli\u003estage-dependent patterns during differentiation, morphogenesis, or lineage commitment\u003c\/li\u003e\n\u003cli\u003eco-patterning with orthogonal markers and control conditions that clarify pathway state\u003c\/li\u003e\n\u003cli\u003etime-matched comparisons so changes reflect biology rather than handling or sampling drift\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for VGR-1. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in VGR-1 reflect biology rather than handling. When interpreting VGR-1, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep VGR-1 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577968107865,"sku":"F2722-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577968140633,"sku":"F2722-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577968173401,"sku":"F2722-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F2722-wb.gif?v=1773600643"},{"product_id":"iap4-antibody-sc-f2849","title":"Survivin Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eIAP4 is a target of interest in many antibody-based workflows. Survivin, also known as BIRC5, is the smallest member of the inhibitor of apoptosis (IAP) protein family, characterized by a single N-terminal baculovirus IAP repeat (BIR) domain and a C-terminal coiled-coil region. It is an evolutionarily conserved protein essential for both cell division and inhibition of apoptosis. Depending on the literature source, IAP4 may also be discussed as Survivin and API4.\u003c\/p\u003e\u003cp\u003eReported cellular context includes centromere, chromosome, cytoplasm, and cytoskeleton, which can matter when signal is compared across treatments or changing cell states. Following IAP4 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eIAP4 is commonly interpreted in the context of cancer, developmental biology, and infectious disease research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans centromere, chromosome, and cytoplasm, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between centromere, chromosome, and cytoplasm across matched conditions\u003c\/li\u003e\n\u003cli\u003echanges associated with proliferative state, oncogenic signaling, or treatment response\u003c\/li\u003e\n\u003cli\u003estage-dependent patterns during differentiation, morphogenesis, or lineage commitment\u003c\/li\u003e\n\u003cli\u003ehost-response changes during infection or pathogen-associated stimulation\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for IAP4. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in IAP4 reflect biology rather than handling. When interpreting IAP4, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep IAP4 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577975841113,"sku":"F2849-20UL","price":139.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577975873881,"sku":"F2849-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577975906649,"sku":"F2849-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F2849-IF.png?v=1773600749"},{"product_id":"ctsl1-antibody-sc-f2971","title":"Cathepsin L\/V\/K\/H Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eCTSL1 is a target of interest in many antibody-based workflows. Cathepsin L is a member of the C1 family of peptidases, a large group of cysteine (thiol) proteases that are essential for various biological processes involving protein breakdown and processing. The enzymatic activity of these proteases relies on a catalytic cysteine residue, typically found within a catalytic dyad or triad. Depending on the literature source, CTSL1 may also be discussed as Cathepsin L\/V\/K\/H and CTSL.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell membrane, cytoplasmic vesicle, lysosome, and membrane, which can matter when signal is compared across treatments or changing cell states. Following CTSL1 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eCTSL1 is commonly interpreted in the context of inflammation research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cell membrane, cytoplasmic vesicle, and lysosome, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cell membrane, cytoplasmic vesicle, and lysosome across matched conditions\u003c\/li\u003e\n\u003cli\u003eresponses associated with cytokine exposure, inflammatory tone, or tissue stress\u003c\/li\u003e\n\u003cli\u003eco-patterning with orthogonal markers and control conditions that clarify pathway state\u003c\/li\u003e\n\u003cli\u003etime-matched comparisons so changes reflect biology rather than handling or sampling drift\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for CTSL1. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in CTSL1 reflect biology rather than handling. When interpreting CTSL1, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep CTSL1 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577988882777,"sku":"F2971-20UL","price":199.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577988915545,"sku":"F2971-100UL","price":489.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577988948313,"sku":"F2971-2X100UL","price":729.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F2971-IF.png?v=1773600853"},{"product_id":"rad52-antibody-sc-f3135","title":"Rad52 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eRAD52 is a human DNA\/RNA-binding protein of 418 amino acids that forms multimeric, ring-shaped oligomers-historically described as heptamers with its highly conserved N-terminal domain (aa 1-208) mediating DNA binding and oligomerization, and its less conserved C-terminal domain containing binding sites for RAD51 and replication protein A (RPA). RAD52 is expressed in the nucleus of proliferating cells, where it plays multifaceted roles in DNA double-strand break repair pathways, most prominently in single-strand annealing (SSA) and as a backup factor for homologous recombination (HR) in BRCA-deficient contexts. Depending on the literature source, RAD52 may also be discussed as DNA repair protein RAD52 homolog.\u003c\/p\u003e\u003cp\u003eReported cellular context includes nucleus, which can matter when signal is compared across treatments or changing cell states. Following RAD52 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eRAD52 is commonly interpreted in the context of dna damage \/ repair research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans nucleus, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003esignal enrichment within nucleus relative to the broader cellular background\u003c\/li\u003e\n\u003cli\u003estress-induced changes after checkpoint activation or genotoxic challenge\u003c\/li\u003e\n\u003cli\u003eco-patterning with orthogonal markers and control conditions that clarify pathway state\u003c\/li\u003e\n\u003cli\u003etime-matched comparisons so changes reflect biology rather than handling or sampling drift\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for RAD52. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in RAD52 reflect biology rather than handling. When interpreting RAD52, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep RAD52 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57578003661145,"sku":"F3135-20UL","price":199.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57578003693913,"sku":"F3135-100UL","price":489.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57578003726681,"sku":"F3135-2X100UL","price":729.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F3135-IF.png?v=1773600948"},{"product_id":"pdgfr-alpha-antibody-sc-f3240","title":"PDGFR α Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003ePDGFR-ALPHA is a target of interest in many antibody-based workflows. PDGFRα (Platelet-derived growth factor receptor alpha) is a type III receptor tyrosine kinase characterized by five extracellular immunoglobulin (Ig)-like domains, a single transmembrane domain, and an intracellular region containing a split kinase domain with a unique inserted sequence, a juxtamembrane domain, and a variable C-terminal tail. Activated by ligand-induced dimerization and autophosphorylation, PDGFRα forms homo- or heterodimers (e. g., with PDGFRβ) upon binding PDGF ligands, excluding PDGF-D. Depending on the literature source, PDGFR-ALPHA may also be discussed as PDGFR alpha and Platelet-derived growth factor receptor alpha; PDGF-R-alpha; PDGFR-alpha; Alpha platelet-derived growth factor receptor; Alpha-type platelet-derived growth factor receptor.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cellmembrane, golgiapparatus, and membrane, which can matter when signal is compared across treatments or changing cell states. Following PDGFR-ALPHA across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003ePDGFR-ALPHA is commonly interpreted in the context of immunology, developmental biology, and cell signaling research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cellmembrane, golgiapparatus, and membrane, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cellmembrane, golgiapparatus, and membrane across matched conditions\u003c\/li\u003e\n\u003cli\u003econtext differences tied to immune-cell state, activation, or lineage composition\u003c\/li\u003e\n\u003cli\u003estage-dependent patterns during differentiation, morphogenesis, or lineage commitment\u003c\/li\u003e\n\u003cli\u003esignal-dependent shifts after ligand, inhibitor, or growth-factor perturbation\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for PDGFR-ALPHA. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in PDGFR-ALPHA reflect biology rather than handling. When interpreting PDGFR-ALPHA, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep PDGFR-ALPHA trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57578011165017,"sku":"F3240-20UL","price":199.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57578011197785,"sku":"F3240-100UL","price":489.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57578011230553,"sku":"F3240-2X100UL","price":729.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F3240-IF.png?v=1773601053"},{"product_id":"trkb-antibody-sc-f3251","title":"TrkB Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eTrkB (Tropomyosin receptor kinase B) is a receptor tyrosine kinase encoded by the NTRK2 gene, primarily activated by neurotrophic factors such as brain-derived neurotrophic factor (BDNF) and neurotrophin-3 (NT-3). It plays a pivotal role in neuronal survival, differentiation, synaptic plasticity, and neuroprotection. Upon ligand binding, TrkB undergoes autophosphorylation on tyrosine residues, activating downstream signalling pathways like MAPK, PI3K, and PLCγ, which regulate cellular processes such as growth, apoptosis, and differentiation.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell membrane, cell projection, cytoplasm, and endosome, which can matter when signal is compared across treatments or changing cell states. Following TRKB across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eTRKB is commonly interpreted in the context of neuroscience and cell signaling research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cell membrane, cell projection, and cytoplasm, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cell membrane, cell projection, and cytoplasm across matched conditions\u003c\/li\u003e\n\u003cli\u003ecompartment-specific patterns relevant to neuronal polarity, transport, or synaptic context\u003c\/li\u003e\n\u003cli\u003esignal-dependent shifts after ligand, inhibitor, or growth-factor perturbation\u003c\/li\u003e\n\u003cli\u003eco-patterning with orthogonal markers and control conditions that clarify pathway state\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for TRKB. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in TRKB reflect biology rather than handling. When interpreting TRKB, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep TRKB trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57578011459929,"sku":"F3251-20UL","price":139.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57578011492697,"sku":"F3251-100UL","price":319.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57578011525465,"sku":"F3251-2X100UL","price":479.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F3251-IF-Mouse-Brain.jpg?v=1773601059"},{"product_id":"arg-1-antibody-sc-f3269","title":"Arginase 1 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eARG-1 is a target of interest in many antibody-based workflows. Arginase 1 (Arg1) is a cytosolic, manganese-dependent enzyme encoded by the ARG1 gene on chromosome 6q23, predominantly expressed in hepatocytes where it catalyzes the hydrolysis of L-arginine to L-ornithine and urea in the final step of the urea cycle, crucial for ammonia detoxification. Arg1 forms a homotrimer, with each subunit containing a binuclear manganese cluster essential for activity. Depending on the literature source, ARG-1 may also be discussed as Arginase 1 and ARG1.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm, which can matter when signal is compared across treatments or changing cell states. Following ARG-1 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eARG-1 is commonly interpreted in the context of immunology, inflammation, and cell signaling research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cytoplasm, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003esignal enrichment within cytoplasm relative to the broader cellular background\u003c\/li\u003e\n\u003cli\u003econtext differences tied to immune-cell state, activation, or lineage composition\u003c\/li\u003e\n\u003cli\u003eresponses associated with cytokine exposure, inflammatory tone, or tissue stress\u003c\/li\u003e\n\u003cli\u003esignal-dependent shifts after ligand, inhibitor, or growth-factor perturbation\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for ARG-1. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in ARG-1 reflect biology rather than handling. When interpreting ARG-1, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep ARG-1 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57578012737881,"sku":"F3269-20UL","price":159.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57578012770649,"sku":"F3269-100UL","price":359.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57578012803417,"sku":"F3269-2X100UL","price":539.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F3269-IF.png?v=1773601078"},{"product_id":"arc-antibody-sc-f3281","title":"Arc Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eArc (Activity-regulated cytoskeleton-associated protein), also known as Arg3. 1, is an immediate early gene product essential for synaptic plasticity, learning, and memory. Structurally, Arc adopts a unique bi-lobar configuration homologous to the capsid domain of HIV Gag protein, reflecting its evolutionary origin from the Ty3\/Gypsy retrotransposon family. Depending on the literature source, ARC may also be discussed as Activity-regulated cytoskeleton-associated protein and hArc.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cellmembrane, cytoplasm, cytoplasmicvesicle, and cytoskeleton, which can matter when signal is compared across treatments or changing cell states. Following ARC across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eARC is commonly interpreted in the context of neuroscience and cell signaling research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cellmembrane, cytoplasm, and cytoplasmicvesicle, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cellmembrane, cytoplasm, and cytoplasmicvesicle across matched conditions\u003c\/li\u003e\n\u003cli\u003ecompartment-specific patterns relevant to neuronal polarity, transport, or synaptic context\u003c\/li\u003e\n\u003cli\u003esignal-dependent shifts after ligand, inhibitor, or growth-factor perturbation\u003c\/li\u003e\n\u003cli\u003eco-patterning with orthogonal markers and control conditions that clarify pathway state\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for ARC. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in ARC reflect biology rather than handling. When interpreting ARC, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep ARC trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57578012836185,"sku":"F3281-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57578012868953,"sku":"F3281-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57578012901721,"sku":"F3281-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F3281-IF.png?v=1773601080"},{"product_id":"htr2c-antibody-sc-f3487","title":"SR-2C Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eHTR2C is a target of interest in many antibody-based workflows. SR-2C (also known as 5-HT2C receptor or serotonin receptor 2C) is a G protein-coupled receptor predominantly found in the central nervous system, with high concentrations in the choroid plexus, hippocampus, amygdala, and hypothalamus. It is composed of seven transmembrane α-helices, an extracellular N-terminus, and an intracellular C-terminus, and it can form homodimers at the cell surface. Depending on the literature source, HTR2C may also be discussed as SR-2C and 5-hydroxytryptamine receptor 2C; 5-HT-2C; 5-HT2C; 5-HTR2C; 5-hydroxytryptamine receptor 1C; Serotonin receptor 2C; HTR1C; HTR2C; 5-HT-1C; 5-HT1C.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell membrane and membrane, which can matter when signal is compared across treatments or changing cell states. Following HTR2C across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eHTR2C is commonly interpreted in the context of neuroscience, endocrinology, and cell signaling research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cell membrane and membrane, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cell membrane and membrane across matched conditions\u003c\/li\u003e\n\u003cli\u003ecompartment-specific patterns relevant to neuronal polarity, transport, or synaptic context\u003c\/li\u003e\n\u003cli\u003eresponses to hormone-dependent signaling or endocrine feedback context\u003c\/li\u003e\n\u003cli\u003esignal-dependent shifts after ligand, inhibitor, or growth-factor perturbation\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for HTR2C. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in HTR2C reflect biology rather than handling. When interpreting HTR2C, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep HTR2C trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57578027090265,"sku":"F3487-20UL","price":199.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57578027123033,"sku":"F3487-100UL","price":489.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57578027155801,"sku":"F3487-2X100UL","price":729.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F3487-wb.gif?v=1773601260"},{"product_id":"fkbp12-antibody-sc-f3489","title":"FKBP12 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eFKBP12 is a cytosolic protein belonging to the immunophilin family, ubiquitously expressed in all tissues and functions primarily as a peptidyl-prolyl cis\/trans isomerase (PPIase), facilitating protein folding and acting as a molecular chaperone. Structurally, FKBP12 contains a single PPIase domain with a compact globular fold and a hydrophobic pocket that binds natural substrates and immunosuppressive drugs such as FK506 and rapamycin. Depending on the literature source, FKBP12 may also be discussed as Peptidyl-prolyl cis-trans isomerase FKBP1A and PPIase FKBP1A.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm, membrane, and sarcoplasmicreticulum, which can matter when signal is compared across treatments or changing cell states. Following FKBP12 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state. In practice, this target is often considered at the family or isoform-group level, so experimental interpretation benefits from matched controls and clear comparison logic.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eFKBP12 is commonly interpreted in the context of immunology and cell signaling research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cytoplasm, membrane, and sarcoplasmicreticulum, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cytoplasm, membrane, and sarcoplasmicreticulum across matched conditions\u003c\/li\u003e\n\u003cli\u003econtext differences tied to immune-cell state, activation, or lineage composition\u003c\/li\u003e\n\u003cli\u003esignal-dependent shifts after ligand, inhibitor, or growth-factor perturbation\u003c\/li\u003e\n\u003cli\u003eco-patterning with orthogonal markers and control conditions that clarify pathway state\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for FKBP12. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in FKBP12 reflect biology rather than handling. When interpreting FKBP12, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep FKBP12 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57578027188569,"sku":"F3489-20UL","price":169.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57578027221337,"sku":"F3489-100UL","price":369.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57578027254105,"sku":"F3489-2X100UL","price":549.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F3489-IF.png?v=1773601261"},{"product_id":"nf-kappab-p65-antibody-sc-f3499","title":"Phospho-NF-κB p65 (Ser468) Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eNf-kappab P65 is a target of interest in many antibody-based workflows. Phospho-NF-κB p65 (Ser468) refers to phosphorylation of the p65 (RelA) subunit of the NF-κB family at serine 468 within its C-terminal transactivation domain. The NF-κB family regulates genes involved in immunity, inflammation, and cell survival through dimeric transcription factor complexes. p65 contains a Rel homology domain responsible for DNA binding and dimerization, and a transactivation domain that mediates transcriptional activation. Depending on the literature source, Nf-kappab P65 may also be discussed as Phospho-NF-kappaB p65 (Ser468) and NFkappaB (Ser468).\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm and nucleus, which can matter when signal is compared across treatments or changing cell states. Following Nf-kappab P65 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eNf-kappab P65 is commonly interpreted in the context of immunology and inflammation research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cytoplasm and nucleus, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cytoplasm and nucleus across matched conditions\u003c\/li\u003e\n\u003cli\u003econtext differences tied to immune-cell state, activation, or lineage composition\u003c\/li\u003e\n\u003cli\u003eresponses associated with cytokine exposure, inflammatory tone, or tissue stress\u003c\/li\u003e\n\u003cli\u003edifferences between total target abundance and site-specific regulation when modified forms are compared\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for Nf-kappab P65. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in Nf-kappab P65 reflect biology rather than handling. When interpreting Nf-kappab P65, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep Nf-kappab P65 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57578027286873,"sku":"F3499-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57578027319641,"sku":"F3499-100UL","price":359.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57578027352409,"sku":"F3499-2X100UL","price":539.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F3499-wb.gif?v=1773601263"},{"product_id":"prkca-prkcb-prkcd-prkce-prkch-prkcq-prkcz-antibody-sc-f3551","title":"Phospho-PKC (pan) (βII Ser660) Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003ePhospho-PKC (pan) (βII Ser660) is a target of interest in many antibody-based workflows. Phospho-PKCβII (Ser660) refers to phosphorylation at the hydrophobic motif site in the C-terminal tail of the conventional protein kinase C beta II isoform, part of the AGC family of serine\/threonine kinases. PKCβII comprises a regulatory domain and a catalytic domain, with Ser660 located in the hydrophobic motif of the C-tail. Depending on the literature source, Phospho-PKC (pan) (βII Ser660) may also be discussed as Phospho-PKC (pan) (betaII Ser660) and PRKCA\/PRKCB\/PRKCD\/PRKCE\/PRKCH\/PRKCQ; Phospho-PKC (pan) (betaII Ser660).\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell membrane, cytoplasm, membrane, and mitochondrion, which can matter when signal is compared across treatments or changing cell states. Following Phospho-PKC (pan) (βII Ser660) across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state. In practice, this target is often considered at the family or isoform-group level, so experimental interpretation benefits from matched controls and clear comparison logic.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003ePhospho-PKC (pan) (βII Ser660) is commonly interpreted in the context of cell signaling research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cell membrane, cytoplasm, and membrane, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cell membrane, cytoplasm, and membrane across matched conditions\u003c\/li\u003e\n\u003cli\u003esignal-dependent shifts after ligand, inhibitor, or growth-factor perturbation\u003c\/li\u003e\n\u003cli\u003edifferences between total target abundance and site-specific regulation when modified forms are compared\u003c\/li\u003e\n\u003cli\u003eco-patterning with orthogonal markers and control conditions that clarify pathway state\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for Phospho-PKC (pan) (βII Ser660). This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in Phospho-PKC (pan) (βII Ser660) reflect biology rather than handling. When interpreting Phospho-PKC (pan) (βII Ser660), it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep Phospho-PKC (pan) (βII Ser660) trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57578032595289,"sku":"F3551-20UL","price":139.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57578032628057,"sku":"F3551-100UL","price":349.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57578032660825,"sku":"F3551-2X100UL","price":519.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F3551-wb.gif?v=1773601303"},{"product_id":"cdk2-antibody-sc-f3552","title":"Phospho-CDK2 (Thr160) Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eThe phosphorylation of CDK2 at threonine 160 (Thr160) is a crucial event for its full activation as a cyclin-dependent kinase, allowing it to regulate cell cycle progression. Thr160 is located in the activation loop (AL) of CDK2, and its phosphorylation stabilizes the AL, aligning substrates for efficient catalysis by reducing its flexibility. Depending on the literature source, CDK2 may also be discussed as Phospho-CDK2 (Thr160).\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm, cytoskeleton, endosome, and nucleus, which can matter when signal is compared across treatments or changing cell states. Following CDK2 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eCDK2 is commonly interpreted in the context of cell cycle and cell signaling research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cytoplasm, cytoskeleton, and endosome, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cytoplasm, cytoskeleton, and endosome across matched conditions\u003c\/li\u003e\n\u003cli\u003ecell-cycle linked differences in abundance, timing, or compartmental enrichment\u003c\/li\u003e\n\u003cli\u003esignal-dependent shifts after ligand, inhibitor, or growth-factor perturbation\u003c\/li\u003e\n\u003cli\u003edifferences between total target abundance and site-specific regulation when modified forms are compared\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for CDK2. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in CDK2 reflect biology rather than handling. When interpreting CDK2, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep CDK2 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57578032693593,"sku":"F3552-20UL","price":199.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57578032726361,"sku":"F3552-100UL","price":489.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57578032759129,"sku":"F3552-2X100UL","price":729.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F3552-IF.png?v=1773601305"},{"product_id":"ret-antibody-sc-f3758","title":"Ret Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eRET (Ret proto-oncogene) is a receptor tyrosine kinase belonging to the cadherin superfamily that transduces extracellular signals into intracellular responses critical for development and tissue homeostasis. Its extracellular domain contains four cadherin-like repeats and a cysteine-rich region, both of which are involved in calcium binding and essential for receptor activation. Depending on the literature source, RET may also be discussed as CDHF12 and CDHR16.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell membrane, endosome, and membrane, which can matter when signal is compared across treatments or changing cell states. Following RET across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eRET is commonly interpreted in the context of cancer, neuroscience, and developmental biology research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cell membrane, endosome, and membrane, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cell membrane, endosome, and membrane across matched conditions\u003c\/li\u003e\n\u003cli\u003echanges associated with proliferative state, oncogenic signaling, or treatment response\u003c\/li\u003e\n\u003cli\u003ecompartment-specific patterns relevant to neuronal polarity, transport, or synaptic context\u003c\/li\u003e\n\u003cli\u003estage-dependent patterns during differentiation, morphogenesis, or lineage commitment\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for RET. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in RET reflect biology rather than handling. When interpreting RET, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep RET trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57578044784985,"sku":"F3758-20UL","price":169.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57578044817753,"sku":"F3758-100UL","price":379.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57578044850521,"sku":"F3758-2X100UL","price":579.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F3758-IF.png?v=1773601451"},{"product_id":"cyp2e1-antibody-sc-f3827","title":"CYP2E1 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eCytochrome P450 2E1 (CYP2E1), an ethanol-metabolizing enzyme, is a member of the cytochrome P450 superfamily of heme-containing monooxygenases that catalyze the oxidative metabolism of a wide range of endogenous and exogenous compounds. Structurally, CYP2E1 is an endoplasmic reticulum-anchored enzyme composed of a hydrophobic N-terminal membrane-binding domain and a conserved catalytic heme-binding domain that facilitates electron transfer from NADPH-cytochrome P450 reductase to substrates. Depending on the literature source, CYP2E1 may also be discussed as 1F12G7 and 4-nitrophenol 2-hydroxylase.\u003c\/p\u003e\u003cp\u003eReported cellular context includes endoplasmic reticulum, membrane, microsome, and mitochondrion, which can matter when signal is compared across treatments or changing cell states. Following CYP2E1 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eCYP2E1 is commonly interpreted in the context of cancer, metabolism, and oxidative stress research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans endoplasmic reticulum, membrane, and microsome, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between endoplasmic reticulum, membrane, and microsome across matched conditions\u003c\/li\u003e\n\u003cli\u003echanges associated with proliferative state, oncogenic signaling, or treatment response\u003c\/li\u003e\n\u003cli\u003eresponses linked to nutrient status, mitochondrial state, or metabolic rewiring\u003c\/li\u003e\n\u003cli\u003eredox-associated shifts that may alter abundance, localization, or pathway coupling\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for CYP2E1. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in CYP2E1 reflect biology rather than handling. When interpreting CYP2E1, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep CYP2E1 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57578049012057,"sku":"F3827-20UL","price":199.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57578049044825,"sku":"F3827-100UL","price":489.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57578049077593,"sku":"F3827-2X100UL","price":729.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F3827-IF-Mouse-Liver.jpg?v=1773601506"}],"url":"https:\/\/absource.de\/collections\/elisa.oembed?page=3","provider":"Absource Diagnostics","version":"1.0","type":"link"}