{"title":"Flow Cytometry","description":"","products":[{"product_id":"dnmt3b-antibody-sc-f0001","title":"DNMT3B Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eDNA Methyltransferase 3 Beta (DNMT3B) is a key enzyme responsible for methylating centromeric, pericentromeric, and subtelomeric repeats. Mammals possess three families of DNA methyltransferases: DNMT1, DNMT2, DNMT3a, and DNMT3b. DNMT3A and DNMT3B exhibit strong expression in embryonic stem cells but reduced levels in adult somatic tissues.\u003c\/p\u003e\u003cp\u003eReported cellular context includes nucleus, which can matter when signal is compared across treatments or changing cell states. Following DNMT3B 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\u003eDNMT3B is commonly interpreted in the context of developmental biology and epigenetics 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\u003estage-dependent patterns during differentiation, morphogenesis, or lineage commitment\u003c\/li\u003e\n\u003cli\u003elinks between target behavior and transcriptional or chromatin-state changes\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\u003eWhere appropriate, pairing DNMT3B with orthogonal markers can improve confidence in interpretation, especially when experimental questions extend from baseline characterization into comparative or perturbation-driven studies.\u003c\/p\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for DNMT3B. 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 DNMT3B reflect biology rather than handling. When interpreting DNMT3B, 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 DNMT3B 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":57577378677081,"sku":"F0001-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577378709849,"sku":"F0001-100UL","price":359.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577378742617,"sku":"F0001-2X100UL","price":539.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0001-IF.png?v=1773598061"},{"product_id":"mapk1-mapk3-antibody-sc-f0002","title":"p44\/42 MAPK (Erk1\/2) Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eMitogen-activated protein kinases, specifically p42\/p44 MAPK (also known as Erk2 and Erk1), are crucial mediators in transmitting signals from the cell surface to the nucleus. The activation of p42\/p44 MAPK, necessary for mitogenic signal transduction, involves a rapid nuclear translocation of these kinases. The p44\/42 MAPK (Erk1\/2) signaling pathway can be activated by various extracellular stimuli, such as mitogens, growth factors, and cytokines. Depending on the literature source, p44\/42 MAPK (Erk1\/2) may also be discussed as p44\/42 MAPK (Erk1\/2) and MAPK3.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell junction, cytoplasm, membrane, and nucleus, which can matter when signal is compared across treatments or changing cell states. Following p44\/42 MAPK (Erk1\/2) 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\u003ep44\/42 MAPK (Erk1\/2) is commonly interpreted in the context of cancer and cell signaling research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cell junction, 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 junction, cytoplasm, 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\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 p44\/42 MAPK (Erk1\/2). 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 p44\/42 MAPK (Erk1\/2) reflect biology rather than handling. When interpreting p44\/42 MAPK (Erk1\/2), 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 p44\/42 MAPK (Erk1\/2) 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":57577378775385,"sku":"F0002-20UL","price":139.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577378808153,"sku":"F0002-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577378840921,"sku":"F0002-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0002-IF.png?v=1773598063"},{"product_id":"gapdh-antibody-sc-f0003","title":"GAPDH Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eGlyceraldehyde-3-phosphate dehydrogenase (GAPDH), an abundant glycolytic enzyme, serves as a crucial intracellular messenger in apoptotic cell death. While traditionally viewed as a housekeeping enzyme, GAPDH also functions in DNA repair as a uracil DNA glycosylase, acts as an Oct-1 coactivator OCA-S for S-phase-dependent histone H2B transcription, and interacts with transfer RNA and DNA. Depending on the literature source, GAPDH may also be discussed as GAPDH Loading Control and Glyceraldehyde-3-Phosphate Dehydrogenase.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm, cytoskeleton, membrane, and nucleus, which can matter when signal is compared across treatments or changing cell states. Following GAPDH 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\u003eGAPDH 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 cytoplasm, cytoskeleton, 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 cytoplasm, cytoskeleton, and membrane across matched conditions\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 GAPDH. 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 GAPDH reflect biology rather than handling. When interpreting GAPDH, 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 GAPDH 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":57577378873689,"sku":"F0003-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577378906457,"sku":"F0003-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577378939225,"sku":"F0003-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0003-IF.png?v=1773598065"},{"product_id":"akt1-akt2-akt3-antibody-sc-f0004","title":"Akt (pan) Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eAkt (pan) is a target of interest in many antibody-based workflows. Akt, also known as PKB or Rac, is pivotal in regulating cell survival and apoptosis. It shares homology with the PKA and PKC families of protein kinases. Akt activation is triggered by various stimuli like insulin, platelet-derived growth factor (PDGF), epidermal growth factor (EGF), and basic fibroblast growth factor (bFGF). Depending on the literature source, Akt (pan) may also be discussed as Akt (pan).\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell membrane, cytoplasm, endosome, and membrane, which can matter when signal is compared across treatments or changing cell states. Following Akt (pan) 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\u003eAkt (pan) is commonly interpreted in the context of cancer, neuroscience, 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 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, cytoplasm, 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\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 Akt (pan). 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 Akt (pan) reflect biology rather than handling. When interpreting Akt (pan), 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 Akt (pan) 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":57577379004761,"sku":"F0004-20UL","price":139.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577379037529,"sku":"F0004-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577379070297,"sku":"F0004-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0004-IHC1.jpg?v=1773598069"},{"product_id":"cdh1-antibody-sc-f0005","title":"E-Cadherin Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eE-cadherin, a tumor suppressor gene, is crucial for cell-cell adhesion in epithelial tissues, primarily localized at adherens junctions. It's encoded by the CDH1 gene, found on chromosome 16q22. 1. Depending on the literature source, CDH1 may also be discussed as E-Cadherin and Cadherin-1.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell junction, cell membrane, cytoplasm, and endosome, which can matter when signal is compared across treatments or changing cell states. Following CDH1 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\u003eCDH1 is commonly interpreted in the context of cancer, 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 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\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\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 CDH1. 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 CDH1 reflect biology rather than handling. When interpreting CDH1, 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 CDH1 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":57577379103065,"sku":"F0005-20UL","price":139.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577379135833,"sku":"F0005-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577379168601,"sku":"F0005-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0005-IF.png?v=1773598071"},{"product_id":"rela-antibody-sc-f0006","title":"NF-κB p65 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eNF-KB is a ubiquitous transcription factor known for its unique activation mechanism and its involvement in both cytoplasmic and nuclear signaling pathways, particularly in response to pathogenic stimuli. It exhibits ubiquitous expression and its various subunits are encoded by mRNA. The active forms of human NF-κB are predominantly dimers consisting of the DNA-binding subunits p50 and RelA. Depending on the literature source, RELA may also be discussed as NF-kappaB p65 and NFkappaB.\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 RELA 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\u003eRELA 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 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\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 RELA. 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 RELA reflect biology rather than handling. When interpreting RELA, 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 RELA 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":57577379365209,"sku":"F0006-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577379397977,"sku":"F0006-100UL","price":359.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577379430745,"sku":"F0006-2X100UL","price":539.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0006-IF.png?v=1773598073"},{"product_id":"mapk1-mapk3-antibody-sc-f0007","title":"Phospho-p44\/42 MAPK (Erk1\/2) (T202\/Y204) Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003ePhospho-p44\/42 MAPK (Erk1\/2) (T202\/Y204) is a target of interest in many antibody-based workflows. Mitogen-activated protein kinases (MAPKs) represent a highly conserved family of serine\/threonine protein kinases implicated in numerous cellular processes such as cell proliferation, differentiation, migration, and apoptosis. Among these, the p44\/42 MAPK (Erk1\/2) signaling pathway is triggered by a wide array of extracellular cues, including mitogens, growth factors, and cytokines. Depending on the literature source, Phospho-p44\/42 MAPK (Erk1\/2) (T202\/Y204) may also be discussed as Phospho-p44\/42 MAPK (Erk1\/2) (T202\/Y204) and Phospho p44 MAPK (Thr 202).\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell junction, cytoplasm, membrane, and nucleus, which can matter when signal is compared across treatments or changing cell states. Following Phospho-p44\/42 MAPK (Erk1\/2) (T202\/Y204) 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-p44\/42 MAPK (Erk1\/2) (T202\/Y204) is commonly interpreted in the context of cancer and cell signaling research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cell junction, 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 junction, cytoplasm, 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\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 Phospho-p44\/42 MAPK (Erk1\/2) (T202\/Y204). 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-p44\/42 MAPK (Erk1\/2) (T202\/Y204) reflect biology rather than handling. When interpreting Phospho-p44\/42 MAPK (Erk1\/2) (T202\/Y204), 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-p44\/42 MAPK (Erk1\/2) (T202\/Y204) 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":57577379463513,"sku":"F0007-20UL","price":169.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577379496281,"sku":"F0007-100UL","price":399.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577379529049,"sku":"F0007-2X100UL","price":599.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0007-IF.png?v=1773598074"},{"product_id":"mmp9-antibody-sc-f0008","title":"MMP9 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eMMP9 is a target of interest in many antibody-based workflows. Matrix metalloproteinases (MMPs) are zinc-dependent endopeptidases involved in tissue remodeling, including physiological and pathophysiological processes. MMP-9, a widely studied MMP, regulates inflammatory and fibrotic remodeling in cardiovascular disease by degrading extracellular matrix (ECM) proteins and activating cytokines and chemokines. Deletion or inhibition of MMP-9 has shown overall benefits in animal models of cardiovascular disease, making MMP-9 expression and activity a common endpoint measurement.\u003c\/p\u003e\u003cp\u003eReported cellular context includes secreted, extracellular space, and extracellular matrix, which can matter when signal is compared across treatments or changing cell states. Following MMP9 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\u003eMMP9 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 secreted, extracellular space, and extracellular matrix, 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 secreted, extracellular space, and extracellular matrix 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 MMP9. 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 MMP9 reflect biology rather than handling. When interpreting MMP9, 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 MMP9 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":57577379561817,"sku":"F0008-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577379594585,"sku":"F0008-100UL","price":359.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577379627353,"sku":"F0008-2X100UL","price":539.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0008-IF.png?v=1773598076"},{"product_id":"actb-antibody-sc-f0012","title":"β-Actin Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eActins are an essential component of the cytoskeleton, with critical roles in a wide range of cellular processes, including cell migration, cell division, and the regulation of gene expression. The two cytoplasmic β-actin and γ-actin isoforms are ubiquitously expressed. Each isoform is the product of a separate gene, with Actb and Actg1 encoding for β-actin and γ-actin, respectively. Depending on the literature source, ACTB may also be discussed as beta-Actin and beta Actin Loading Control.\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 ACTB 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\u003eACTB 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, 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\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 ACTB. 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 ACTB reflect biology rather than handling. When interpreting ACTB, 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 ACTB 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":57577379758425,"sku":"F0012-20UL","price":139.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577379791193,"sku":"F0012-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577379823961,"sku":"F0012-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0012-IF.png?v=1773598078"},{"product_id":"v5-tag-antibody-sc-f0016","title":"V5-Tag Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eV5 Tag is a target of interest in many antibody-based workflows. The V5-tag is a short, 14-amino acid epitope tag originally derived from a prokaryotic source and widely used for recombinant protein detection and purification. Structurally, it contains an equal number of positively and negatively charged residues, yielding a pI of 5. 85 and no net charge at physiological pH, with three proline residues that confer a partially ordered and stable core while remaining largely unstructured. Depending on the literature source, V5 Tag may also be discussed as V5-Tag.\u003c\/p\u003e\u003cp\u003eFollowing V5 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\u003eV5 Tag is commonly interpreted in the context of aging research, and readouts are often stronger when a study separates expression changes from broader shifts in cell state. 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\u003econtext changes tied to cellular senescence, long-term stress adaptation, or tissue aging\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 V5 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 V5 Tag reflect biology rather than handling. When interpreting V5 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 V5 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":57577379856729,"sku":"F0016-20UL","price":199.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577379889497,"sku":"F0016-100UL","price":489.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577379922265,"sku":"F0016-2X100UL","price":729.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0016-wb.gif?v=1773598080"},{"product_id":"pcna-antibody-sc-f0018","title":"PCNA Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eProliferating cell nuclear antigen (PCNA), the eukaryotic DNA sliding clamp, comprises a ring-shaped homo-trimer encircling double-stranded DNA. Its primary function lies in providing high processivity to replicative DNA polymerases. Serving as a mobile platform on DNA, it facilitates the recruitment of various proteins engaged in DNA replication, repair, and recombination at replication forks. Depending on the literature source, PCNA may also be discussed as Proliferating Cell Nuclear Antigen.\u003c\/p\u003e\u003cp\u003eReported cellular context includes nucleus, which can matter when signal is compared across treatments or changing cell states. Following PCNA 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\u003ePCNA is commonly interpreted in the context of immunology, 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\u003econtext differences tied to immune-cell state, activation, or lineage composition\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\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 PCNA. 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 PCNA reflect biology rather than handling. When interpreting PCNA, 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 PCNA 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":57577380053337,"sku":"F0018-20UL","price":169.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577380086105,"sku":"F0018-100UL","price":379.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577380118873,"sku":"F0018-2X100UL","price":569.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0018-IHC1.jpg?v=1773598083"},{"product_id":"tp53-antibody-sc-f0020","title":"p53 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003ep53 is a tumor suppressor protein encoded by the TP53 gene, acting as a transcription factor that regulates cell cycle arrest, apoptosis, and DNA repair to maintain genomic stability. Structurally, it is a 393-amino acid protein with an N-terminal transactivation domain (TAD), a proline-rich domain (PRD), a central DNA-binding domain (DBD), a tetramerization domain (TET), and a C-terminal regulatory domain (CTD). p53 is primarily expressed in the nucleus, where its levels are tightly controlled by negative regulators like MDM2 and MDMX, which promote its degradation. Depending on the literature source, TP53 may also be discussed as p53.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm, cytoskeleton, endoplasmic reticulum, and mitochondrion, which can matter when signal is compared across treatments or changing cell states. Following TP53 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\u003eTP53 is commonly interpreted in the context of cancer, metabolism, and dna damage \/ repair research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cytoplasm, cytoskeleton, 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 cytoplasm, cytoskeleton, 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\u003estress-induced changes after checkpoint activation or genotoxic challenge\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 TP53. 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 TP53 reflect biology rather than handling. When interpreting TP53, 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 TP53 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":57577380151641,"sku":"F0020-20UL","price":139.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577380184409,"sku":"F0020-100UL","price":319.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577380217177,"sku":"F0020-2X100UL","price":479.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0020-IF.png?v=1773598084"},{"product_id":"cdk2-antibody-sc-f0022","title":"Cdk2 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eCyclin-dependent kinase 2, also known as Cdk2 or cell division protein kinase 2, is a serine\/threonine protein kinase involved in regulating the G1\/S transition, initiating DNA synthesis, and controlling exit from the S phase. It is distributed across various cellular compartments, including the nucleus, cytoplasm, and endosomes. Depending on the literature source, CDK2 may also be discussed as CDKN2 and Cell division protein kinase 2.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm, cytoskeleton, microtubule, and centrosome, 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 signaling 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\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 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":57577380249945,"sku":"F0022-20UL","price":169.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577380282713,"sku":"F0022-100UL","price":399.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577380315481,"sku":"F0022-2X100UL","price":599.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0022-IF.png?v=1773598086"},{"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":"mcl1-antibody-sc-f0024","title":"MCL1 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eMCL1 is a target of interest in many antibody-based workflows. Mcl-1, an anti-apoptotic member of the Bcl-2 family, is initially identified in the ML-1 human myeloid leukemia cell line during differentiation induced by phorbol esters along the monocyte\/macrophage pathway. Like other Bcl-2 family members, Mcl-1 localizes to mitochondria, interacts with and counteracts pro-apoptotic Bcl-2 family proteins, and inhibits apoptosis triggered by various cytotoxic stimuli. Depending on the literature source, MCL1 may also be discussed as Mcl-1.\u003c\/p\u003e\u003cp\u003eReported cellular context includes membrane, cytoplasm, mitochondrion, and nucleus, which can matter when signal is compared across treatments or changing cell states. Following MCL1 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\u003eMCL1 is commonly interpreted in the context of cancer, immunology, and developmental biology research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans membrane, cytoplasm, 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 membrane, cytoplasm, 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\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\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 MCL1. 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 MCL1 reflect biology rather than handling. When interpreting MCL1, 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 MCL1 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":57577381265753,"sku":"F0024-20UL","price":169.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577381298521,"sku":"F0024-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577381331289,"sku":"F0024-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0024-IF.png?v=1773598088"},{"product_id":"egfr-antibody-sc-f0053","title":"EGF Receptor Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eEpidermal growth factor (EGF) receptor is a transmembrane tyrosine kinase that belongs to the ERBB family of tyrosine kinase receptors. EGFR is a 170-kDa single-pass transmembrane tyrosine kinase that undergoes homo- or heterodimerization and enzymatic activation following ligand binding which result in the trans-(auto)-phosphorylation of multiple Tyr residues in the COOH-terminal tail of the molecule and serve as binding sites for cytosolic signaling proteins containing Src homology 2 (SH2) domains. Depending on the literature source, EGFR may also be discussed as EGF Receptor and Epidermal Growth Factor Receptor.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell membrane, endoplasmic reticulum, endosome, and golgi apparatus, which can matter when signal is compared across treatments or changing cell states. Following EGFR 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\u003eEGFR is commonly interpreted in the context of cancer, 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 cell membrane, endoplasmic reticulum, 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, endoplasmic reticulum, 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\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 EGFR. 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 EGFR reflect biology rather than handling. When interpreting EGFR, 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 EGFR 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":57577381953881,"sku":"F0053-20UL","price":159.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577381986649,"sku":"F0053-100UL","price":359.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577382019417,"sku":"F0053-2X100UL","price":539.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0053-IF.png?v=1773598099"},{"product_id":"histone-h3-antibody-sc-f0057","title":"Histone H3 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eHistone H3 is a target of interest in many antibody-based workflows. Modulation of chromatin structure is pivotal in regulating transcription in eukaryotes. The nucleosome, comprising DNA wound around eight core histone proteins (two each of H2A, H2B, H3, and H4), serves as the fundamental unit of chromatin. Acetylation of H3 at Lys9 is particularly influential in histone deposition and chromatin assembly in certain organisms.\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 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\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 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":57577382248793,"sku":"F0057-20UL","price":159.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577382281561,"sku":"F0057-100UL","price":359.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577382314329,"sku":"F0057-2X100UL","price":539.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0057-IHC1.jpg?v=1773598103"},{"product_id":"tuba1b-antibody-sc-f0063","title":"α-Tubulin Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eTUBA1B is a target of interest in many antibody-based workflows. Highly conserved α- and β-tubulin heterodimers form dynamic microtubules critical for cellular functions like structural support, transport pathways, and cell division. These microtubules are essential for cell growth and division. Tubulin also plays a crucial role in the nervous system, impacting health and neurodegenerative diseases like Parkinson’s and Alzheimer’s. Depending on the literature source, TUBA1B may also be discussed as alpha-Tubulin.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm, cytoskeleton, and microtubule, which can matter when signal is compared across treatments or changing cell states. Following TUBA1B 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\u003eTUBA1B 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 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\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\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 TUBA1B. 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 TUBA1B reflect biology rather than handling. When interpreting TUBA1B, 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 TUBA1B 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":57577382543705,"sku":"F0063-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577382576473,"sku":"F0063-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577382609241,"sku":"F0063-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0063-IHC1.jpg?v=1773598108"},{"product_id":"rho12-antibody-sc-f0072","title":"Rho A Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eRHO12 is a target of interest in many antibody-based workflows. RhoA is a member of the Rho family of small GTPases that functions as a molecular switch to regulate cytoskeletal dynamics, cell shape, motility, and adhesion. RhoA encompasses a conserved GTPase domain that cycles between an inactive GDP-bound and an active GTP-bound state, controlling its interaction with downstream effectors. Depending on the literature source, RHO12 may also be discussed as Rho A and Transforming protein RhoA.\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 RHO12 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\u003eRHO12 is commonly interpreted in the context of neuroscience, cardiovascular, 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, 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\u003echanges linked to vascular, contractile, or hemodynamic cell-state cues\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 RHO12. 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 RHO12 reflect biology rather than handling. When interpreting RHO12, 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 RHO12 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":57577382740313,"sku":"F0072-20UL","price":139.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577382773081,"sku":"F0072-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577382805849,"sku":"F0072-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0072-IF.png?v=1773598110"},{"product_id":"actin-antibody-sc-f0082","title":"Actin Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eActin, a ubiquitous protein, plays a critical role in forming the filaments that constitute the cytoskeleton. In vertebrates, there are three groups of actin isoforms: alpha, beta, and gamma. Alpha-actins are primarily found in muscle tissues and are crucial components of the contractile machinery. Depending on the literature source, ACTIN may also be discussed as Pan-Actin.\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 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\u003eACTIN 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 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 ACTIN reflect biology rather than handling. When interpreting 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 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":57577383035225,"sku":"F0082-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577383067993,"sku":"F0082-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577383100761,"sku":"F0082-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0082-IHC1.jpg?v=1773598115"},{"product_id":"ccne1-antibody-sc-f0095","title":"Cyclin E1 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eCyclin E1, encoded by the CCNE1 gene, belongs to the cyclin family and plays a crucial role in regulating several cellular processes by forming complexes with cyclin-dependent kinases (CDKs). It primarily pairs with CDK2 to facilitate the phosphorylation of key substrates involved in cell cycle progression. Depending on the literature source, CCNE1 may also be discussed as Cyclin E1 and Cyclin E.\u003c\/p\u003e\u003cp\u003eReported cellular context includes nucleus, which can matter when signal is compared across treatments or changing cell states. Following CCNE1 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\u003eCCNE1 is commonly interpreted in the context of cancer, 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 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\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\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 CCNE1. 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 CCNE1 reflect biology rather than handling. When interpreting CCNE1, 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 CCNE1 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":57577383133529,"sku":"F0095-20UL","price":169.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577383166297,"sku":"F0095-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577383199065,"sku":"F0095-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0095-IHC1.jpg?v=1773598117"},{"product_id":"hif1a-antibody-sc-f0101","title":"HIF-1α Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eHIF1A is a target of interest in many antibody-based workflows. Hypoxia-inducible factor (HIF) is a transcriptional complex crucial for regulating gene expression in response to oxygen levels. The HIF1 complex is made up of two subunits, HIF-1α and HIF-1β, both of which are basic helix-loop-helix proteins belonging to the PAS (Per, ARNT, Sim) family. HIF1 controls the transcription of a wide range of genes that aid in adapting to hypoxic conditions, including those involved in angiogenesis, erythropoiesis, cell cycle regulation, metabolism, and apoptosis. Depending on the literature source, HIF1A may also be discussed as HIF-1alpha and Hypoxia Inducible Factor 1 alpha.\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 HIF1A 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\u003eHIF1A 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 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\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 HIF1A. 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 HIF1A reflect biology rather than handling. When interpreting HIF1A, 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 HIF1A 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":57577383264601,"sku":"F0101-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577383297369,"sku":"F0101-100UL","price":359.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577383330137,"sku":"F0101-2X100UL","price":539.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0101-IF.png?v=1773598119"},{"product_id":"rbfox3-antibody-sc-f0103","title":"NeuN Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eNEUN, also known as Fox-3, RBFOX3 (RNA binding protein, fox-1), or Fox-1 homolog C, is a 350 amino acid protein that contains one RRM (RNA recognition motif) domain. NEUN (Fox-3) is localized to both the nucleus and cytoplasm and contains an RNA recognition motif that functions as a splicing regulator and regulates alternative splicing events. Depending on the literature source, RBFOX3 may also be discussed as NeuN and RBFOX3\/NeuN.\u003c\/p\u003e\u003cp\u003eReported cellular context includes nucleus and cytoplasm, which can matter when signal is compared across treatments or changing cell states. Following RBFOX3 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\u003eRBFOX3 is commonly interpreted in the context of neuroscience and developmental biology research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans nucleus 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 nucleus 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\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\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 RBFOX3. 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 RBFOX3 reflect biology rather than handling. When interpreting RBFOX3, 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 RBFOX3 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":57577383362905,"sku":"F0103-20UL","price":169.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577383395673,"sku":"F0103-100UL","price":379.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577383428441,"sku":"F0103-2X100UL","price":569.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0103-IF.png?v=1773598119"},{"product_id":"oct4-antibody-sc-f0104","title":"Oct4 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eOct4 (octamer-binding transcription factor 4), encoded by the highly conserved POU5F1 gene, is a key transcription factor critical for maintaining pluripotency in early embryonic development and germ cell lineages. Structurally, Oct4 is a 324-amino acid protein comprising three main domains: an N-terminal transactivation domain, a central POU-specific DNA-binding domain that recognizes the octamer motif (5′-ATTTGCAT-3′), and a C-terminal transactivation domain. Depending on the literature source, OCT4 may also be discussed as OCT3 and OTF3.\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 OCT4 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\u003eOCT4 is commonly interpreted in the context of cancer, developmental biology, and stem cell 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\u003estage-dependent patterns during differentiation, morphogenesis, or lineage commitment\u003c\/li\u003e\n\u003cli\u003estate transitions between self-renewal, priming, and differentiation\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 OCT4. 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 OCT4 reflect biology rather than handling. When interpreting OCT4, 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 OCT4 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":57577383461209,"sku":"F0104-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577383493977,"sku":"F0104-100UL","price":319.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577383526745,"sku":"F0104-2X100UL","price":479.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0104-IF.png?v=1773598122"},{"product_id":"sqstm1-antibody-sc-f0106","title":"SQSTM1 \/ p62 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eSQSTM1\/p62, a 62-kDa protein expressed widely across various tissues, is a key autophagy adaptor, binding ubiquitin and autophagy substrates through its ubiquitin-associated domain and LC3-interacting region, respectively. It regulates mitochondrial turnover via mitophagy and serves as a crucial regulator of mtDNA expression machinery, inducing mtDNA expression in renal tubular epithelial cells through p38-dependent upregulation of mitochondrial ribosomal protein L12 (MRPL12). Depending on the literature source, SQSTM1 may also be discussed as SQSTM1 \/ p62 and p62 (Sequestosome-1).\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm, cytosol, endosome, and lysosome, which can matter when signal is compared across treatments or changing cell states. Following SQSTM1 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\u003eSQSTM1 is commonly interpreted in the context of metabolism, autophagy, and cell signaling research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cytoplasm, cytosol, 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, cytosol, and endosome across matched conditions\u003c\/li\u003e\n\u003cli\u003eresponses linked to nutrient status, mitochondrial state, or metabolic rewiring\u003c\/li\u003e\n\u003cli\u003einterpretation alongside flux, cargo handling, or lysosomal 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 SQSTM1. 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 SQSTM1 reflect biology rather than handling. When interpreting SQSTM1, 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 SQSTM1 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":57577383625049,"sku":"F0106-20UL","price":139.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577383657817,"sku":"F0106-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577383690585,"sku":"F0106-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0106-IF.png?v=1773598124"},{"product_id":"rps27a-uba52-ubb-ubc-antibody-sc-f0109","title":"Ubiquitin Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eUbiquitin, a small protein consisting of 76 amino acids, plays a pivotal role in cellular processes through ubiquitylation, where it forms an isopeptide bond with an internal lysine residue of the substrate, typically facilitated by the C-terminal glycine (glycine 76) of ubiquitin. This process is integral to the ubiquitin-proteasome pathway, a vital cellular defense mechanism responsible for identifying and eliminating faulty proteins. Depending on the literature source, Ubiquitin may also be discussed as Ubiquitin and Ub.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm, nucleus, and mitochondrion outer membrane, which can matter when signal is compared across treatments or changing cell states. Following Ubiquitin 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\u003eUbiquitin is commonly interpreted in the context of apoptosis research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cytoplasm, nucleus, and mitochondrion outer 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 cytoplasm, nucleus, and mitochondrion outer membrane across matched conditions\u003c\/li\u003e\n\u003cli\u003eseparation of survival-associated changes from stress or death-associated readouts\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 Ubiquitin. 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 Ubiquitin reflect biology rather than handling. When interpreting Ubiquitin, 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 Ubiquitin 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":57577383821657,"sku":"F0109-20UL","price":169.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577383854425,"sku":"F0109-100UL","price":399.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577383887193,"sku":"F0109-2X100UL","price":599.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0109-IF.png?v=1773598125"},{"product_id":"vcl-antibody-sc-f0110","title":"Vinculin Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eVinculin (VCL) is a cytoskeletal protein associated with cell-cell and cell-extracellular matrix adherens-type junctions. Vinculin comprises three major domains- an N-terminal head, a flexible proline-rich hinge (neck) region, and a C-terminal tail domain. Vinculin activation results from conformational rearrangements of these domains. Depending on the literature source, VCL may also be discussed as Vinculin.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell membrane, cell junction, cytoplasm, and cytoskeleton, which can matter when signal is compared across treatments or changing cell states. Following VCL 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\u003eVCL is commonly interpreted in the context of cancer 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, 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\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\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 VCL. 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 VCL reflect biology rather than handling. When interpreting VCL, 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 VCL 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":57577383919961,"sku":"F0110-20UL","price":169.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577383952729,"sku":"F0110-100UL","price":379.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577383985497,"sku":"F0110-2X100UL","price":569.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0110-wb.gif?v=1773598127"},{"product_id":"eif4ebp1-antibody-sc-f0128","title":"4E-BP1 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eEIF4EBP1 is a target of interest in many antibody-based workflows. Eukaryotic translation initiation factor 4E (eIF4E)-binding protein 1 (4E-BP1) belongs to a family of proteins that suppress translation and is a well-known target of the mechanistic target of rapamycin (mTOR) signaling pathway. Multiple residues on 4E-BP1 undergo phosphorylation in vivo. While phosphorylation by FRAP\/mTOR at Thr37 and Thr46 does not impede the binding of 4E-BP1 to eIF4E, it is thought to prepare 4E-BP1 for subsequent phosphorylation at Ser65 and Thr70. Depending on the literature source, EIF4EBP1 may also be discussed as 4E-BP1 and Eukaryotic translation initiation factor 4E-binding protein 1.\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 EIF4EBP1 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\u003eEIF4EBP1 is commonly interpreted in the context of cancer, angiogenesis, 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\u003echanges associated with proliferative state, oncogenic signaling, or treatment response\u003c\/li\u003e\n\u003cli\u003edifferences related to endothelial activation, vessel remodeling, or growth-factor exposure\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 EIF4EBP1. 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 EIF4EBP1 reflect biology rather than handling. When interpreting EIF4EBP1, 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 EIF4EBP1 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":57577384116569,"sku":"F0128-20UL","price":139.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577384149337,"sku":"F0128-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577384182105,"sku":"F0128-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0128-IHC1.jpg?v=1773598130"},{"product_id":"creb-antibody-sc-f0133","title":"CREB Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eCREB, a bZIP transcription factor, is capable of activating target genes by binding to cAMP response elements. It serves as a mediator for signals from various physiological stimuli, leading to the regulation of diverse cellular responses. Although expressed in multiple tissues, CREB exerts significant regulatory influence within the nervous system. Depending on the literature source, CREB may also be discussed as CREB-1.\u003c\/p\u003e\u003cp\u003eReported cellular context includes nucleus, which can matter when signal is compared across treatments or changing cell states. Following CREB 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\u003eCREB 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 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\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 CREB. 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 CREB reflect biology rather than handling. When interpreting CREB, 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 CREB 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":57577384313177,"sku":"F0133-20UL","price":139.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577384345945,"sku":"F0133-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577384378713,"sku":"F0133-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0133-IHC1.jpg?v=1773598134"},{"product_id":"caspase3-antibody-sc-f0135","title":"Cleaved Caspase3 (Asp175) Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eCASPASE3 is a target of interest in many antibody-based workflows. Caspase-3, a member of the Cysteine-ASPartic proteASES family (cysteine proteases), is primarily recognized for its role in cleaving specific target proteins. It is widely expressed and is instrumental in executing apoptosis, triggered by both extrinsic and intrinsic factors. Beyond apoptosis, caspase-3 also regulates the growth and maintenance of normal and cancerous cells and tissues in multicellular organisms. Depending on the literature source, CASPASE3 may also be discussed as Cleaved Caspase3 (Asp175) and Active Caspase-3.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm, which can matter when signal is compared across treatments or changing cell states. Following CASPASE3 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\u003eCASPASE3 is commonly interpreted in the context of apoptosis 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\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\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 CASPASE3. 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 CASPASE3 reflect biology rather than handling. When interpreting CASPASE3, 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 CASPASE3 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":57577384411481,"sku":"F0135-20UL","price":159.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577384444249,"sku":"F0135-100UL","price":389.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577384477017,"sku":"F0135-2X100UL","price":579.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0135-IF.jpg?v=1773598134"},{"product_id":"parp-antibody-sc-f0136","title":"Cleaved PARP (Asp214) Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003ePARP, a 116-kDa nuclear poly (ADP-ribose) polymerase, plays a pivotal role in DNA repair during environmental stress. It was subsequently shown to be cleaved into 89- and 24-kDa fragments during drug-induced apoptosis in various cells. This cleavage inactivates the enzyme by destroying its ability to respond to DNA strand breaks. Depending on the literature source, PARP may also be discussed as Cleaved PARP (Asp214).\u003c\/p\u003e\u003cp\u003eReported cellular context includes chromosome, cytoplasm, and nucleus, which can matter when signal is compared across treatments or changing cell states. Following PARP 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\u003ePARP is commonly interpreted in the context of dna damage \/ repair and apoptosis research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans chromosome, 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 chromosome, cytoplasm, and nucleus across matched conditions\u003c\/li\u003e\n\u003cli\u003estress-induced changes after checkpoint activation or genotoxic challenge\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 PARP. 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 PARP reflect biology rather than handling. When interpreting PARP, 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 PARP 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":57577384509785,"sku":"F0136-20UL","price":169.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577384542553,"sku":"F0136-100UL","price":429.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577384575321,"sku":"F0136-2X100UL","price":639.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0136-wb.gif?v=1773598136"},{"product_id":"ccnd1-antibody-sc-f0137","title":"Cyclin D1 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eCyclin D1 is a 36-kDa protein encoded by the CCND1 gene on chromosome 11q13. It plays a crucial role in regulating the cell cycle, particularly in promoting the transition from G1 to S phase. Cyclin D1 forms a complex with CDK4\/6, which phosphorylates retinoblastoma (RB) protein, releasing E2F transcription factors to drive cell proliferation. Depending on the literature source, CCND1 may also be discussed as Cyclin D1 and Cyclin D.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm, membrane, and nucleus, which can matter when signal is compared across treatments or changing cell states. Following CCND1 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\u003eCCND1 is commonly interpreted in the context of cancer and cell cycle research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cytoplasm, membrane, 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, membrane, 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\u003ecell-cycle linked differences in abundance, timing, or compartmental enrichment\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 CCND1. 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 CCND1 reflect biology rather than handling. When interpreting CCND1, 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 CCND1 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":57577384640857,"sku":"F0137-20UL","price":159.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577384673625,"sku":"F0137-100UL","price":359.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577384706393,"sku":"F0137-2X100UL","price":539.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0137-IF.png?v=1773598137"},{"product_id":"foxo1-antibody-sc-f0141","title":"FoxO1 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eFOXO1 is a target of interest in many antibody-based workflows. The forkhead box O (FoxO) transcription factors are pivotal players in numerous physiological and pathological processes, spanning apoptosis, cell cycle regulation, stress response, glucose metabolism, cellular differentiation, development, and tumor suppression. The potent functions of FoxOs are intricately regulated through various mechanisms, encompassing posttranslational modifications such as phosphorylation, acetylation, methylation, and ubiquitination, subcellular localization, and direct protein-protein interactions. Depending on the literature source, FOXO1 may also be discussed as FKHR\/FOXO1 and FOXO1A.\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 FOXO1 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\u003eFOXO1 is commonly interpreted in the context of 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\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\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 FOXO1. 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 FOXO1 reflect biology rather than handling. When interpreting FOXO1, 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 FOXO1 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":57577384771929,"sku":"F0141-20UL","price":139.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577384804697,"sku":"F0141-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577384837465,"sku":"F0141-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0141-IHC1.jpg?v=1773598141"},{"product_id":"gsk3b-antibody-sc-f0142","title":"GSK-3β Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eGSK3B is a target of interest in many antibody-based workflows. Glycogen synthase kinase-3 (GSK-3) is a crucial serine\/threonine kinase that regulates various cellular functions, including metabolism, transcription, translation, cell growth, and apoptosis. It is present in two similar isoforms, GSK-3α and GSK-3β, which are highly expressed in the brain. GSK-3α and GSK-3β have distinct N-terminal regions but share approximately 98% homology in the internal kinase domain. Depending on the literature source, GSK3B may also be discussed as GSK-3beta.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell membrane, cytoplasm, membrane, and nucleus, which can matter when signal is compared across treatments or changing cell states. Following GSK3B 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\u003eGSK3B is commonly interpreted in the context of cancer, neuroscience, 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 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\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\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 GSK3B. 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 GSK3B reflect biology rather than handling. When interpreting GSK3B, 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 GSK3B 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":57577384870233,"sku":"F0142-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577384903001,"sku":"F0142-100UL","price":359.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577384935769,"sku":"F0142-2X100UL","price":539.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0142-IF.png?v=1773598143"},{"product_id":"map1lc3a-map1lc3b-antibody-sc-f0144","title":"LC3A\/B Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eLC3A\/B is a target of interest in many antibody-based workflows. Light Chain 3 (LC3), initially identified as a subunit of microtubule-associated protein 1 light chain 3 (MAP1LC3), is a crucial component of autophagy pathways. LC3, homologous to yeast Atg8, is involved in hybrid degradation pathways and exists as three isoforms in humans (LC3A, LC3B, and LC3C) and two in mice (LC3A and LC3B). Depending on the literature source, LC3A\/B may also be discussed as LC3A\/B and MAP1A\/MAP1B LC3 A.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm, cytoplasmic vesicle, cytoskeleton, and membrane, which can matter when signal is compared across treatments or changing cell states. Following LC3A\/B 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\u003eLC3A\/B is commonly interpreted in the context of autophagy research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cytoplasm, cytoplasmic vesicle, 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, cytoplasmic vesicle, and cytoskeleton across matched conditions\u003c\/li\u003e\n\u003cli\u003einterpretation alongside flux, cargo handling, or lysosomal 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 LC3A\/B. 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 LC3A\/B reflect biology rather than handling. When interpreting LC3A\/B, 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 LC3A\/B 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":57577384968537,"sku":"F0144-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577385001305,"sku":"F0144-100UL","price":359.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577385034073,"sku":"F0144-2X100UL","price":539.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0144-IF.png?v=1773598146"},{"product_id":"lc3b-antibody-sc-f0145","title":"LC3B Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eLC3B is a target of interest in many antibody-based workflows. Autophagy is a highly conserved process in which proteins and organelles undergo degradation. These damaged components are subsequently removed and recycled through lysosomes. Regulated by various autophagy-related genes (Atgs), autophagy ultimately leads to the formation of the autophagosome.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm, cytoplasmic vesicle, cytoskeleton, and membrane, which can matter when signal is compared across treatments or changing cell states. Following LC3B 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\u003eLC3B is commonly interpreted in the context of autophagy research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cytoplasm, cytoplasmic vesicle, 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, cytoplasmic vesicle, and cytoskeleton across matched conditions\u003c\/li\u003e\n\u003cli\u003einterpretation alongside flux, cargo handling, or lysosomal 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 LC3B. 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 LC3B reflect biology rather than handling. When interpreting LC3B, 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 LC3B 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":57577385066841,"sku":"F0145-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577385099609,"sku":"F0145-100UL","price":359.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577385132377,"sku":"F0145-2X100UL","price":539.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0145-IF.png?v=1773598148"},{"product_id":"creb-antibody-sc-f0154","title":"Phospho-CREB (Ser133) Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003ePhospho-CREB (Ser133) is the phosphorylated form of the cAMP response element-binding protein (CREB), a bZIP transcription factor essential for gene regulation in response to extracellular signals. Structurally, CREB contains a basic region-leucine zipper (bZIP) domain for DNA binding and dimerization, a kinase-inducible domain (KID) where Ser133 resides, and Q1\/Q2 domains for transcriptional activation. Depending on the literature source, CREB may also be discussed as Phospho-CREB (Ser133) and CREB (phospho S133).\u003c\/p\u003e\u003cp\u003eReported cellular context includes nucleus, which can matter when signal is compared across treatments or changing cell states. Following CREB 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\u003eCREB 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 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\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\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 CREB. 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 CREB reflect biology rather than handling. When interpreting CREB, 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 CREB 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":57577385263449,"sku":"F0154-20UL","price":159.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577385296217,"sku":"F0154-100UL","price":389.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577385328985,"sku":"F0154-2X100UL","price":579.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0154-IF.png?v=1773598155"},{"product_id":"p-rela-antibody-sc-f0155","title":"Phospho-NF-κB p65 (Ser536) Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eP-RELA is a target of interest in many antibody-based workflows. NF-κB is activated by various infectious agents and inflammatory cytokines, playing a central role in inflammation control and immunosuppression. The mammalian NF-κB family comprises five transcription factors: p65 (RelA), RelB, c-Rel, p105\/p50 (NF-κB1), and p100\/p52 (NF-κB2), with p50 and p52 generated by proteolytic processing of p105 and p100. Depending on the literature source, P-RELA may also be discussed as Phospho-NF-kappaB p65 (Ser536) and NF-kB p65 (phospho S536).\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 P-RELA 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\u003eP-RELA 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 P-RELA. 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 P-RELA reflect biology rather than handling. When interpreting P-RELA, 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 P-RELA 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":57577385394521,"sku":"F0155-20UL","price":159.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577385427289,"sku":"F0155-100UL","price":389.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577385460057,"sku":"F0155-2X100UL","price":579.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0155-IF.png?v=1773598157"},{"product_id":"stat3-antibody-sc-f0157","title":"Phospho-STAT3 (Tyr705) Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eSTAT3 is a transcription factor and intracellular signalling protein activated by a range of cytokines, growth factors, and intracellular kinases. It is fundamental to the development and function of various body systems and is essential for life. In the immune system, STAT3 is crucial for the maturation of immune cells, especially T and B cells. Depending on the literature source, STAT3 may also be discussed as Phospho-STAT3 (Tyr705) and p-Stat3.\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 STAT3 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\u003eSTAT3 is commonly interpreted in the context of cancer, 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 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\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 STAT3. 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 STAT3 reflect biology rather than handling. When interpreting STAT3, 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 STAT3 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":57577385525593,"sku":"F0157-20UL","price":169.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577385558361,"sku":"F0157-100UL","price":419.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577385591129,"sku":"F0157-2X100UL","price":629.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0157-2-wb.gif?v=1773598158"},{"product_id":"h3k27me3-antibody-sc-f0165","title":"Histone H3 (tri methyl Lys27) Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eH3K27ME3 is a target of interest in many antibody-based workflows. Histone H3 is a DNA-binding protein present in the chromatin of all eukaryotic cells. Along with four core histone proteins, H3 forms the nucleosome structure by binding to DNA. Histones undergo various post-translational modifications, such as methylation, acetylation, and phosphorylation, on the protruding N-terminal tail, influencing cellular processes. Depending on the literature source, H3K27ME3 may also be discussed as Histone H3 (tri methyl Lys27) and Histone H3 (tri methyl K27).\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 H3K27ME3 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\u003eH3K27ME3 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 H3K27ME3. 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 H3K27ME3 reflect biology rather than handling. When interpreting H3K27ME3, 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 H3K27ME3 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":57577393717593,"sku":"F0165-20UL","price":159.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577393750361,"sku":"F0165-100UL","price":389.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577393783129,"sku":"F0165-2X100UL","price":579.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0165-IF.png?v=1773598165"},{"product_id":"tubb-antibody-sc-f0167","title":"β-Tubulin Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eTUBB is a target of interest in many antibody-based workflows. The α and β monomers of tubulin exist as isotypes differing in their amino acid sequence encoded by different genes and α\/β heterodimers of tubulin polymerize into microtubules, which are indispensable for cell division and growth. Tubulin also plays an important role in the nervous system, both in health and in neurodegenerative diseases such as Parkinson’s and Alzheimer’s. Depending on the literature source, TUBB may also be discussed as beta-Tubulin and beta Tubulin Loading Control.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm, cytoskeleton, and microtubule, which can matter when signal is compared across treatments or changing cell states. Following TUBB 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\u003eTUBB 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 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\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 TUBB. 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 TUBB reflect biology rather than handling. When interpreting TUBB, 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 TUBB 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":57577398075737,"sku":"F0167-20UL","price":139.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577398108505,"sku":"F0167-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577398141273,"sku":"F0167-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0167-IF.png?v=1773598165"},{"product_id":"jun-antibody-sc-f0168","title":"c-Jun Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003ec-Jun, a member of the Jun family, includes JunB and JunD, forming a component of the transcription factor activator protein-1 (AP-1). AP-1 comprises dimers of Fos, Jun, and ATF family members, which bind to and activate transcription at TRE\/AP-1 elements. c-JUN transcription factors are essential for mouse embryonic development. Depending on the literature source, JUN may also be discussed as c-Jun.\u003c\/p\u003e\u003cp\u003eReported cellular context includes nucleus, which can matter when signal is compared across treatments or changing cell states. Following JUN 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\u003eJUN 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 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\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 JUN. 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 JUN reflect biology rather than handling. When interpreting JUN, 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 JUN 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":57577401712985,"sku":"F0168-20UL","price":139.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577401745753,"sku":"F0168-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577401778521,"sku":"F0168-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0168-IF.png?v=1773598169"},{"product_id":"mtor-antibody-sc-f0169","title":"mTOR Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eThe mammalian target of rapamycin (mTOR) is a serine-threonine protein kinase with broad regulatory roles in cell growth, proliferation, metabolism, protein synthesis, and autophagy. In the brain, mTOR is vital for synaptic plasticity, learning, and cortical development. It forms two functional complexes, mTORC1 and mTORC2.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm, cytoplasmic vesicle, endoplasmic reticulum, and golgi apparatus, which can matter when signal is compared across treatments or changing cell states. Following MTOR 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\u003eMTOR is commonly interpreted in the context of neuroscience, metabolism, and cell signaling research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cytoplasm, cytoplasmic vesicle, 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 cytoplasm, cytoplasmic vesicle, and endoplasmic reticulum 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 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 MTOR. 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 MTOR reflect biology rather than handling. When interpreting MTOR, 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 MTOR 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":57577410789721,"sku":"F0169-20UL","price":139.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577410822489,"sku":"F0169-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577410855257,"sku":"F0169-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0169-IF.png?v=1773598171"},{"product_id":"cdkn1a-antibody-sc-f0170","title":"p21 Waf1\/Cip1 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eCDKN1A is a target of interest in many antibody-based workflows. Protein p21 (Cip1\/Waf1) is a cyclin-dependent kinase inhibitor that belongs to the CIP\/Kip family of CDK inhibitors (CKIs). Based on the localization, the p21(Cip1\/Waf1) protein executes various functions in the cell. In the nucleus, p21 (Cip1\/Waf1) binds to and inhibit the activity of CDK1 and CDK2, thereby blocks the transition from the G1 phase to the S phase or from the G2 phase to mitosis following DNA damage, facilitating DNA repair processes. Depending on the literature source, CDKN1A may also be discussed as p21 Waf1\/Cip1 and p21.\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 CDKN1A 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\u003eCDKN1A is commonly interpreted in the context of cancer, 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 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\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\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 CDKN1A. 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 CDKN1A reflect biology rather than handling. When interpreting CDKN1A, 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 CDKN1A 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":57577418621273,"sku":"F0170-20UL","price":139.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577418654041,"sku":"F0170-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577418686809,"sku":"F0170-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0170-IF.png?v=1773598174"},{"product_id":"mapk11-mapk12-mapk14-antibody-sc-f0171","title":"p38 MAPK Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003ep38 MAPK is a target of interest in many antibody-based workflows. The p38 family, highly conserved among species, comprises mitogen-activated protein kinases (MAPKs) involved in coordinating cellular responses to various stressful stimuli. p38α, originally identified as a 38 kDa protein tyrosine-phosphorylated upon LPS stimulation, shares homology with the Saccharomyces cerevisiae osmotic response protein kinase HOG1. It's also known as cytokine suppressive drug binding protein (CSBP) due to its targeting by anti-inflammatory compounds, and as reactivating kinase (RK) for its activation of MK2. Depending on the literature source, p38 MAPK may also be discussed as p38 MAPK and MAPK 14.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm, nucleus, and mitochondrion, which can matter when signal is compared across treatments or changing cell states. Following p38 MAPK 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\u003ep38 MAPK is commonly interpreted in the context of 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, nucleus, 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, nucleus, and mitochondrion across matched conditions\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\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 p38 MAPK. 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 p38 MAPK reflect biology rather than handling. When interpreting p38 MAPK, 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 p38 MAPK 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":57577423307097,"sku":"F0171-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577423339865,"sku":"F0171-100UL","price":359.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577423372633,"sku":"F0171-2X100UL","price":539.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0171-IHC1.jpg?v=1773598178"},{"product_id":"nos2-antibody-sc-f0177","title":"iNOS Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eNOS2 is a target of interest in many antibody-based workflows. Inducible nitric oxide synthase (iNOS) is one of three enzymes that produce nitric oxide (NO) from l-arginine. iNOS-derived NO is crucial in physiological processes like blood pressure regulation, wound repair, and host defense, as well as in pathological conditions such as inflammation, infection, cancer, liver cirrhosis, and diabetes. The iNOS gene, located on chromosome 17, shares sequence similarity with nNOS and eNOS. iNOS is commonly linked to malignant diseases and is stimulated by cytokines like TNF-alpha, IL-1, and IFN-gamma. Depending on the literature source, NOS2 may also be discussed as iNOS and iNOS\/NOS Type II.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm, which can matter when signal is compared across treatments or changing cell states. Following NOS2 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\u003eNOS2 is commonly interpreted in the context of immunology, inflammation, and infectious disease 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\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 NOS2. 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 NOS2 reflect biology rather than handling. When interpreting NOS2, 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 NOS2 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":57577423602009,"sku":"F0177-20UL","price":169.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577423634777,"sku":"F0177-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577423667545,"sku":"F0177-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0177-wb.gif?v=1773598182"},{"product_id":"axl-antibody-sc-f0178","title":"Axl Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eAXL, a member of the TAM family of receptor tyrosine kinases (RTKs) along with TYRO3 and MER, plays a crucial role in tumor progression and metastasis, with its expression linked to poor survival in various cancers. GAS6 binds all TAM receptors, favoring AXL, while protein S binds only MER and TYRO3.\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 AXL 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\u003eAXL is commonly interpreted in the context of cancer 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\u003echanges associated with proliferative state, oncogenic signaling, or treatment response\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 AXL. 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 AXL reflect biology rather than handling. When interpreting AXL, 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 AXL 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":57577423700313,"sku":"F0178-20UL","price":139.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577423733081,"sku":"F0178-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577423765849,"sku":"F0178-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0178-IF.png?v=1773598184"},{"product_id":"rps6-antibody-sc-f0198","title":"Phospho-S6 Ribosomal Protein (S235\/236) Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eRPS6 is a target of interest in many antibody-based workflows. Growth factors and mitogens effectively stimulate sustained cell growth and proliferation by upregulating mRNA translation. Activation of p70 S6 kinase and subsequent phosphorylation of S6 ribosomal protein are key events in this process. Phosphorylation of S6 ribosomal protein leads to enhanced translation of mRNA transcripts containing an oligopyrimidine tract in their 5' untranslated regions. Depending on the literature source, RPS6 may also be discussed as Phospho-S6 Ribosomal Protein (S235\/236) and Phospho-S6 Ribosomal Protein (Ser235\/236).\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 RPS6 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\u003eRPS6 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 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 linked to nutrient status, mitochondrial state, or metabolic rewiring\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 RPS6. 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 RPS6 reflect biology rather than handling. When interpreting RPS6, 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 RPS6 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":57577424290137,"sku":"F0198-20UL","price":169.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577424322905,"sku":"F0198-100UL","price":419.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577424355673,"sku":"F0198-2X100UL","price":629.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0198-IF.png?v=1773598195"},{"product_id":"stat1-antibody-sc-f0199","title":"Phospho-STAT1 (Tyr701) Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eSTAT1 (Signal Transducer and Activator of Transcription 1) is a crucial transcription factor that plays a key role in mediating cellular responses to various cytokines, especially interferons (IFNs). When activated, STAT1 translocates to the nucleus and regulates gene expression related to immune responses, cell growth, and apoptosis. Depending on the literature source, STAT1 may also be discussed as Phospho-STAT1 (Tyr701) and p-Stat1.\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 STAT1 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\u003eSTAT1 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 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\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 STAT1. 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 STAT1 reflect biology rather than handling. When interpreting STAT1, 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 STAT1 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":57577424388441,"sku":"F0199-20UL","price":169.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577424421209,"sku":"F0199-100UL","price":389.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577424453977,"sku":"F0199-2X100UL","price":579.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0199-IF.png?v=1773598197"},{"product_id":"stat3-antibody-sc-f0200","title":"Stat3 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eSignal transducer and activator of transcription 3 (STAT3) is a transcription factor belonging to the STAT protein family. Upon stimulation by cytokines and growth factors, STAT3 undergoes phosphorylation by receptor-associated Janus kinases (JAK), leading to its dimerization and translocation to the nucleus where it functions as a transcriptional activator.\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 STAT3 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\u003eSTAT3 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 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\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 STAT3. 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 STAT3 reflect biology rather than handling. When interpreting STAT3, 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 STAT3 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":57577424486745,"sku":"F0200-20UL","price":139.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577424519513,"sku":"F0200-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577424552281,"sku":"F0200-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0200-IHC1.jpg?v=1773598198"}],"url":"https:\/\/absource.de\/collections\/flow-cytometry.oembed?page=2","provider":"Absource Diagnostics","version":"1.0","type":"link"}