{"title":"Oncology","description":"","products":[{"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":"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":"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":"rps6kb1-antibody-sc-f0011","title":"p70 S6 Kinase Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eRPS6KB1 is a target of interest in many antibody-based workflows. The p70 Ribosomal protein S6 kinase 1 (S6K1, p70S6K) is part of the AGC subfamily of serine\/threonine protein kinases, which includes cyclic AMP-dependent protein kinase, cyclic GMP-dependent protein kinase, and protein kinase C. The S6K family is located on chromosome 17q23. Through alternative splicing and different translational start sites, the human S6K1 gene produces two isoforms: p70 and p85. Depending on the literature source, RPS6KB1 may also be discussed as p70 S6 Kinase and p70 S6 kinase alpha.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm, membrane, mitochondrion, and mitochondrion outer membrane, which can matter when signal is compared across treatments or changing cell states. Following RPS6KB1 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\u003eRPS6KB1 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, membrane, and mitochondrion, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cytoplasm, membrane, and mitochondrion across matched conditions\u003c\/li\u003e\n\u003cli\u003echanges associated with proliferative state, oncogenic signaling, or treatment response\u003c\/li\u003e\n\u003cli\u003eresponses linked to nutrient status, mitochondrial state, or metabolic rewiring\u003c\/li\u003e\n\u003cli\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 RPS6KB1. 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 RPS6KB1 reflect biology rather than handling. When interpreting RPS6KB1, 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 RPS6KB1 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":57577379660121,"sku":"F0011-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577379692889,"sku":"F0011-100UL","price":369.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577379725657,"sku":"F0011-2X100UL","price":549.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0011-IHC1.jpg?v=1773598077"},{"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":"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":"nes-antibody-sc-f0031","title":"Nestin Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eNestin, originally identified in neural stem cells, is an intermediate filament cytoskeletal protein found in various tissues and stem or progenitor cells, including pancreatic islets, skeletal muscle satellite cells, and the heart. It is also expressed in several malignancies, such as osteosarcoma, neuroblastoma, glioma, melanoma, pancreatic and prostate cancers, as well as in tumor vasculature. Depending on the literature source, NES may also be discussed as Nestin.\u003c\/p\u003e\u003cp\u003eReported cellular context includes intermediate filament, which can matter when signal is compared across treatments or changing cell states. Following NES 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\u003eNES is commonly interpreted in the context of cancer, neuroscience, and stem cell biology research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans intermediate filament, 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 intermediate filament 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\u003ecompartment-specific patterns relevant to neuronal polarity, transport, or synaptic context\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 NES. 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 NES reflect biology rather than handling. When interpreting NES, 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 NES 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":57577381560665,"sku":"F0031-20UL","price":169.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577381593433,"sku":"F0031-100UL","price":399.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577381626201,"sku":"F0031-2X100UL","price":599.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0031-IF-Mouse-Brain.jpg?v=1773598093"},{"product_id":"bax-antibody-sc-f0037","title":"Bax Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eThe mechanisms of apoptosis contribute to understanding the pathologies associated with uncontrolled cell growth or death. Apoptosis involves two major pathways: the extrinsic or death receptor pathway and the intrinsic or mitochondrial pathway. The intrinsic pathway is regulated by the Bcl-2 (B-cell lymphoma 2) family of proteins, which can be classified based on their anti-apoptotic (e. g., Bcl-2, Bcl-x, Bcl-w, Mcl-1, and A1\/Bfl-1) or pro-apoptotic (e. g., Bax, Bak, and Bok\/Mtd) actions. Depending on the literature source, BAX may also be discussed as NT.\u003c\/p\u003e\u003cp\u003eReported cellular context includes mitochondrion outer membrane and cytoplasm, which can matter when signal is compared across treatments or changing cell states. Following BAX across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eBAX is commonly interpreted in the context of cancer, metabolism, and apoptosis research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans mitochondrion outer membrane and cytoplasm, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between mitochondrion outer membrane and cytoplasm across matched conditions\u003c\/li\u003e\n\u003cli\u003echanges associated with proliferative state, oncogenic signaling, or treatment response\u003c\/li\u003e\n\u003cli\u003eresponses linked to nutrient status, mitochondrial state, or metabolic rewiring\u003c\/li\u003e\n\u003cli\u003eseparation of survival-associated changes from stress or death-associated readouts\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for BAX. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in BAX reflect biology rather than handling. When interpreting BAX, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep BAX trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577381757273,"sku":"F0037-20UL","price":139.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577381790041,"sku":"F0037-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577381822809,"sku":"F0037-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0037-IHC1.jpg?v=1773598096"},{"product_id":"becn1-antibody-sc-f0038","title":"Beclin 1 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eBECN1 is a target of interest in many antibody-based workflows. BECLIN1, a well-established regulator of autophagy, collaborates with other proteins to form Class III Phosphoinositide 3-Kinase (PI3K) complexes, generating phosphorylated phosphatidylinositol (PtdIns), crucial for autophagy and membrane trafficking processes. While primarily recognized as a haploinsufficient tumor suppressor, BECLIN1 plays pivotal roles in various physiological contexts, including murine embryo development, dauer development, immunity, neuronal and cardiac health. Depending on the literature source, BECN1 may also be discussed as Beclin 1 and Beclin.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm, golgi apparatus, endosome, and endoplasmic reticulum, which can matter when signal is compared across treatments or changing cell states. Following BECN1 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\u003eBECN1 is commonly interpreted in the context of cancer, neuroscience, and developmental biology research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cytoplasm, golgi apparatus, 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, golgi apparatus, and endosome across matched conditions\u003c\/li\u003e\n\u003cli\u003echanges associated with proliferative state, oncogenic signaling, or treatment response\u003c\/li\u003e\n\u003cli\u003ecompartment-specific patterns relevant to neuronal polarity, transport, or synaptic context\u003c\/li\u003e\n\u003cli\u003estage-dependent patterns during differentiation, morphogenesis, or lineage commitment\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for BECN1. 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 BECN1 reflect biology rather than handling. When interpreting BECN1, 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 BECN1 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":57577381855577,"sku":"F0038-20UL","price":139.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577381888345,"sku":"F0038-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577381921113,"sku":"F0038-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0038-IHC1.jpg?v=1773598098"},{"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":"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":"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":"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":"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":"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":"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":"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":"ccnd3-antibody-sc-f0173","title":"Cyclin D3 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eD-type cyclins, including cyclins D1, D2, and D3, are key recipients of mitogenic and oncogenic signals in mammalian cells. Cyclin D3, encoded by the CCND3 gene, is crucial in the cell cycle machinery and is expressed broadly in proliferating cells. Its gene is rearranged, and the protein is overexpressed in various human lymphoid malignancies, such as diffuse large B cell lymphomas and multiple myelomas, suggesting its role in these diseases. Depending on the literature source, CCND3 may also be discussed as Cyclin D3 and Cyclin D3\/CCND3.\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 CCND3 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\u003eCCND3 is commonly interpreted in the context of cancer, immunology, 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\u003econtext differences tied to immune-cell state, activation, or lineage composition\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 CCND3. 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 CCND3 reflect biology rather than handling. When interpreting CCND3, 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 CCND3 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":57577423405401,"sku":"F0173-20UL","price":139.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577423438169,"sku":"F0173-100UL","price":319.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577423470937,"sku":"F0173-2X100UL","price":479.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0173-IHC1.jpg?v=1773598180"},{"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":"ar-antibody-sc-f0220","title":"Androgen Receptor Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eThe androgen receptor (AR) is a nuclear receptor that acts as a transcription factor, regulating the development and growth of the prostate. It becomes activated through phosphorylation and dimerization upon binding to its ligand. Structurally, the AR consists of three main functional domains: the N-terminal transcriptional regulation domain, the DNA binding domain (DBD), and the ligand binding domain. Depending on the literature source, AR may also be discussed as Androgen Receptor.\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 AR 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\u003eAR is commonly interpreted in the context of cancer, endocrinology, 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 to hormone-dependent signaling or endocrine feedback context\u003c\/li\u003e\n\u003cli\u003esignal-dependent shifts after ligand, inhibitor, or growth-factor perturbation\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for AR. 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 AR reflect biology rather than handling. When interpreting AR, 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 AR 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":57577432416601,"sku":"F0220-20UL","price":169.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577432449369,"sku":"F0220-100UL","price":379.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577432482137,"sku":"F0220-2X100UL","price":569.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0220-IF.png?v=1773598207"},{"product_id":"fasn-antibody-sc-f0225","title":"Fatty Acid Synthase Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eFatty acid synthetase (FASN) is a multifunctional enzyme responsible for synthesizing long-chain saturated fatty acids from acetyl-CoA and malonyl-CoA, utilizing NADPH. As an active homodimer, FASN possesses seven distinct catalytic activities and is involved in lipid production, primarily in the liver for distribution to metabolically active tissues or storage in adipose tissue. Depending on the literature source, FASN may also be discussed as Fatty Acid Synthase.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm, which can matter when signal is compared across treatments or changing cell states. Following FASN 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\u003eFASN is commonly interpreted in the context of cancer and metabolism 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\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\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 FASN. 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 FASN reflect biology rather than handling. When interpreting FASN, 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 FASN 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":57577432908121,"sku":"F0225-20UL","price":139.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577432940889,"sku":"F0225-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577432973657,"sku":"F0225-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0225-IHC1.jpg?v=1773598215"},{"product_id":"erbb2-antibody-sc-f0227","title":"HER2\/ErbB2 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eErbB2, a member of the ErbB family of receptor tyrosine kinases (RTKs), comprises an extracellular ligand-binding domain, a single transmembrane domain, an uninterrupted tyrosine kinase domain, and a cytoplasmic tail. It plays a central role in both ligand binding and signal transduction. ErbB2 homodimers activate downstream signaling pathways, resulting in Erk2 and Akt phosphorylation. Depending on the literature source, ERBB2 may also be discussed as HER2\/ErbB2 and ErbB2 \/ HER2.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell membrane, cell projection, cytoplasm, and endosome, which can matter when signal is compared across treatments or changing cell states. Following ERBB2 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\u003eERBB2 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, 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\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 ERBB2. 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 ERBB2 reflect biology rather than handling. When interpreting ERBB2, 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 ERBB2 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":57577433006425,"sku":"F0227-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577433039193,"sku":"F0227-100UL","price":319.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577433071961,"sku":"F0227-2X100UL","price":479.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0227-IHC1.jpg?v=1773598216"},{"product_id":"jak2-antibody-sc-f0231","title":"JAK2 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eJanus kinases (Jaks) are crucial non-receptor tyrosine kinases involved in cytokine receptor signaling. The Jak family comprises four members: Jak1, Jak2, Jak3, and Tyk2, with Jak2 playing a key role in regulating cellular growth and proliferation. Jak2 mutations are frequently observed in hematological cancers, including myeloid and lymphoid leukemia, and myeloproliferative neoplasms (MPN), resulting in constitutive kinase activation.\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 JAK2 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\u003eJAK2 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 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\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 JAK2. 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 JAK2 reflect biology rather than handling. When interpreting JAK2, 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 JAK2 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":57577433465177,"sku":"F0231-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577433497945,"sku":"F0231-100UL","price":359.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577433530713,"sku":"F0231-2X100UL","price":539.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0231-IHC1.jpg?v=1773598223"},{"product_id":"lef1-antibody-sc-f0234","title":"LEF1 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eLymphoid enhancer-binding factor 1 (LEF1) is part of the T-cell Factor (TCF)\/LEF1 family of high-mobility group transcription factors and serves as a downstream mediator of the Wnt\/β-catenin signaling pathway. LEF1 can also regulate gene transcription independently of this pathway. It plays a crucial role in stem cell maintenance and organ development, particularly through its involvement in epithelial-mesenchymal transition (EMT).\u003c\/p\u003e\u003cp\u003eReported cellular context includes nucleus, which can matter when signal is compared across treatments or changing cell states. Following LEF1 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\u003eLEF1 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 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\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 LEF1. 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 LEF1 reflect biology rather than handling. When interpreting LEF1, 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 LEF1 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":57577433596249,"sku":"F0234-20UL","price":139.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577433629017,"sku":"F0234-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577433661785,"sku":"F0234-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0234-IF.png?v=1773598225"},{"product_id":"stk11-antibody-sc-f0235","title":"LKB1 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eLKB1 (STK11) is a type of protein known as a serine\/threonine kinase and serves as a crucial tumor suppressor. It plays a significant role in regulating cell structure, apoptosis (cell death), and maintaining energy balance within cells by controlling various downstream kinases. Initially identified as the gene responsible for Peutz-Jeghers syndrome (PJS), a condition characterized by the presence of hamartomatous polyps and distinctive pigmentation of the oral mucosa, LKB1 has since been implicated in a range of malignancies, including lung, gastrointestinal, pancreatic, and breast cancers. Depending on the literature source, STK11 may also be discussed as LKB1.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm, membrane, mitochondrion, and nucleus, which can matter when signal is compared across treatments or changing cell states. Following STK11 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\u003eSTK11 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, membrane, and mitochondrion, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cytoplasm, membrane, and mitochondrion across matched conditions\u003c\/li\u003e\n\u003cli\u003echanges associated with proliferative state, oncogenic signaling, or treatment response\u003c\/li\u003e\n\u003cli\u003eresponses linked to nutrient status, mitochondrial state, or metabolic rewiring\u003c\/li\u003e\n\u003cli\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 STK11. 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 STK11 reflect biology rather than handling. When interpreting STK11, 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 STK11 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":57577433760089,"sku":"F0235-20UL","price":169.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577433792857,"sku":"F0235-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577433825625,"sku":"F0235-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0235-IHC1.jpg?v=1773598226"},{"product_id":"cfl1-antibody-sc-f0244","title":"Phospho-Cofilin (Ser3) Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eCFL1 is a target of interest in many antibody-based workflows. Phospho-cofilin (Ser3) is a crucial regulatory protein that plays a significant role in actin dynamics, impacting cellular processes such as motility, morphology, and apoptosis. When cofilin is phosphorylated at serine 3 (Ser3), its ability to bind actin is inhibited, thus regulating the polymerization and depolymerization of actin filaments. Depending on the literature source, CFL1 may also be discussed as Phospho-Cofilin (Ser3) and Cofilin (phospho S3).\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 CFL1 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\u003eCFL1 is commonly interpreted in the context of cancer 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\u003echanges associated with proliferative state, oncogenic signaling, or treatment response\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 CFL1. 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 CFL1 reflect biology rather than handling. When interpreting CFL1, 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 CFL1 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":57577434579289,"sku":"F0244-20UL","price":159.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577434612057,"sku":"F0244-100UL","price":389.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577434644825,"sku":"F0244-2X100UL","price":579.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0244-IF.png?v=1773598238"},{"product_id":"erbb2-antibody-sc-f0245","title":"Phospho-HER2\/ErbB2 (Tyr1221\/1222) Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eERBB2 is a target of interest in many antibody-based workflows. The human epidermal growth factor receptor (HER) family drives several human cancers by regulating cell growth, survival, and differentiation through diverse signal transduction pathways. Comprising HER-1, HER-2, HER-3, and HER-4 (ErbB1-4), these receptors feature extracellular ligand binding sites, transmembrane segments, and intracellular domains with tyrosine kinase activity. Depending on the literature source, ERBB2 may also be discussed as Phospho-HER2\/ErbB2 (Tyr1221\/1222) and Phospho HER2 (Tyr 1221).\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell membrane, cell projection, cytoplasm, and endosome, which can matter when signal is compared across treatments or changing cell states. Following ERBB2 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\u003eERBB2 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, 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\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 ERBB2. 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 ERBB2 reflect biology rather than handling. When interpreting ERBB2, 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 ERBB2 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":57577434743129,"sku":"F0245-20UL","price":159.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577434775897,"sku":"F0245-100UL","price":389.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577434808665,"sku":"F0245-2X100UL","price":579.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0245-IHC1.jpg?v=1773598243"},{"product_id":"histone-h3-antibody-sc-f0246","title":"Phospho-Histone H3 (Ser10) Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003ePhospho-Histone H3 (Ser 10) is a dynamic post-translational modification by phosphorylation at the 10th serine residue on the N-terminal tail of histone H3, involved in chromosome condensation during mitosis and transcriptional activation of immediate-early (IE) genes in response to growth factors, stress, and oncogenic signals. Structurally, it occurs on the amino-terminal tail of histone H3, neutralizing positive charges and weakening histone-DNA interactions to promote chromatin remodeling. Depending on the literature source, Histone H3 may also be discussed as Phospho-Histone H3 (Ser10) and Histone H3 (phospho S10).\u003c\/p\u003e\u003cp\u003eReported cellular context includes chromosome, nucleosome core, and nucleus, which can matter when signal is compared across treatments or changing cell states. Following Histone H3 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eHistone H3 is commonly interpreted in the context of cancer, neuroscience, and epigenetics research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans chromosome, nucleosome core, and nucleus, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between chromosome, nucleosome core, and nucleus across matched conditions\u003c\/li\u003e\n\u003cli\u003echanges associated with proliferative state, oncogenic signaling, or treatment response\u003c\/li\u003e\n\u003cli\u003ecompartment-specific patterns relevant to neuronal polarity, transport, or synaptic context\u003c\/li\u003e\n\u003cli\u003elinks between target behavior and transcriptional or chromatin-state changes\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for Histone H3. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in Histone H3 reflect biology rather than handling. When interpreting Histone H3, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep Histone H3 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577434841433,"sku":"F0246-20UL","price":169.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577434874201,"sku":"F0246-100UL","price":419.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577434906969,"sku":"F0246-2X100UL","price":629.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0246-IF.png?v=1773598244"},{"product_id":"pras40-antibody-sc-f0252","title":"Phospho-PRAS40 (Thr246) Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eThe proline-rich Akt substrate of 40 kDa (PRAS40) is a key substrate of Akt and an integral component of the mammalian target of rapamycin complex 1 (mTORC1). Positioned at the intersection of the PI3K\/Akt and mTOR signaling pathways, PRAS40 is phosphorylated in response to growth factors and other stimuli, subsequently influencing the activation of these pathways. Depending on the literature source, PRAS40 may also be discussed as Phospho-PRAS40 (Thr246).\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm, which can matter when signal is compared across treatments or changing cell states. Following PRAS40 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\u003ePRAS40 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 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\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 PRAS40. 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 PRAS40 reflect biology rather than handling. When interpreting PRAS40, 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 PRAS40 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":57577435038041,"sku":"F0252-20UL","price":169.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577435070809,"sku":"F0252-100UL","price":399.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577435103577,"sku":"F0252-2X100UL","price":599.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0252-IHC1.jpg?v=1773598247"},{"product_id":"rictor-antibody-sc-f0260","title":"Rictor Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eRICTOR is a target of interest in many antibody-based workflows. Receptor tyrosine kinases (RTKs) are cellular receptors that respond to signals from growth factors and hormones, playing a vital role in cell communication and controlling processes like proliferation and survival. RTKs consist of three parts: a ligand-binding region, a transmembrane helix, and a cytoplasmic domain with tyrosine kinase activity.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytosol and golgi apparatus, which can matter when signal is compared across treatments or changing cell states. Following RICTOR 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\u003eRICTOR 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 cytosol and golgi apparatus, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cytosol and golgi apparatus across matched conditions\u003c\/li\u003e\n\u003cli\u003echanges associated with proliferative state, oncogenic signaling, or treatment response\u003c\/li\u003e\n\u003cli\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 RICTOR. 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 RICTOR reflect biology rather than handling. When interpreting RICTOR, 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 RICTOR 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":57577435529561,"sku":"F0260-20UL","price":139.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577435562329,"sku":"F0260-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577435595097,"sku":"F0260-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0260-IHC1.jpg?v=1773598254"},{"product_id":"birc5-antibody-sc-f0264","title":"Survivin Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eSurvivin, an inhibitor of apoptosis protein (IAP), encoded by the BIRC5 gene, is a versatile regulator with distinct expression patterns in normal and cancer cells. As the smallest IAP in humans, survivin, located on chromosome 17, inhibits apoptotic and autophagic cell death. It suppresses pro-caspase 9 alongside HBXIP, blocking death receptor signaling. Depending on the literature source, BIRC5 may also be discussed as Survivin.\u003c\/p\u003e\u003cp\u003eReported cellular context includes centromere, chromosome, cytoplasm, and cytoskeleton, which can matter when signal is compared across treatments or changing cell states. Following BIRC5 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\u003eBIRC5 is commonly interpreted in the context of cancer, angiogenesis, and cell cycle research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans centromere, chromosome, and cytoplasm, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between centromere, chromosome, and cytoplasm across matched conditions\u003c\/li\u003e\n\u003cli\u003echanges associated with proliferative state, oncogenic signaling, or treatment response\u003c\/li\u003e\n\u003cli\u003edifferences related to endothelial activation, vessel remodeling, or growth-factor exposure\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 BIRC5. 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 BIRC5 reflect biology rather than handling. When interpreting BIRC5, 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 BIRC5 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":57577435922777,"sku":"F0264-20UL","price":139.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577435955545,"sku":"F0264-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577435988313,"sku":"F0264-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0264-IF.png?v=1773598259"},{"product_id":"zeb1-antibody-sc-f0266","title":"ZEB1 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eThe ZEB family comprises zinc-finger and homeobox domain-containing transcription factors, with two members identified in mammals: ZEB1 (also known as δ-EF1, TCF8, AREB6) and ZEB2 (SIP1). Both ZEB1 and ZEB2 feature two distinct zinc-finger domains along with a homeodomain. While primarily acting as transcriptional repressors, ZEB proteins can also activate transcription, contingent upon the DNA context and cell type.\u003c\/p\u003e\u003cp\u003eReported cellular context includes nucleus, which can matter when signal is compared across treatments or changing cell states. Following ZEB1 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\u003eZEB1 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 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\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 ZEB1. 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 ZEB1 reflect biology rather than handling. When interpreting ZEB1, 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 ZEB1 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":57577436152153,"sku":"F0266-20UL","price":139.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577436184921,"sku":"F0266-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577436217689,"sku":"F0266-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0266-wb.gif?v=1773598261"},{"product_id":"notch1-antibody-sc-f0277","title":"Cleaved Notch1 (Val1744) Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eNOTCH1 is a target of interest in many antibody-based workflows. Notch proteins are transmembrane receptors that form heterodimeric proteins, comprising a large extracellular ligand-binding domain, a single-pass transmembrane domain, and a smaller cytoplasmic subunit called the Notch intracellular domain (NICD). When interacting with ligands from the Delta-Serrate-Lag2 (DSL) family, the heterodimers undergo dissociation, followed by proteolytic cleavage and release of NICD. Depending on the literature source, NOTCH1 may also be discussed as Cleaved Notch1 (Val1744).\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell membrane, membrane, and nucleus, which can matter when signal is compared across treatments or changing cell states. Following NOTCH1 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\u003eNOTCH1 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, 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 cell membrane, 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\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 NOTCH1. 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 NOTCH1 reflect biology rather than handling. When interpreting NOTCH1, 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 NOTCH1 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":57577437167961,"sku":"F0277-20UL","price":159.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577437200729,"sku":"F0277-100UL","price":389.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577437233497,"sku":"F0277-2X100UL","price":579.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0277-wb.gif?v=1773598281"},{"product_id":"hsp90aa1-hsp90ab1-antibody-sc-f0283","title":"HSP90 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eHeat Shock Protein 90 (Hsp90) is a highly conserved molecular chaperone found in all eukaryotic cells, playing a critical role in maintaining protein homeostasis (proteostasis) by assisting in the folding, stabilization, activation, and refolding of various client proteins, particularly those involved in cellular signalling and stress responses. Structurally, Hsp90 is a dimeric protein composed of three main domains: the N-terminal domain (NTD), which binds and hydrolyzes ATP; the middle domain (MD), which mediates client protein binding; and the C-terminal domain (CTD), which interacts with cochaperones and regulatory proteins. Depending on the literature source, HSP90 may also be discussed as HSP90 and Heat Shock Protein 90.\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 HSP90 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\u003eHSP90 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, 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\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 HSP90. 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 HSP90 reflect biology rather than handling. When interpreting HSP90, 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 HSP90 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":57577437659481,"sku":"F0283-20UL","price":139.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577437692249,"sku":"F0283-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577437725017,"sku":"F0283-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0283-IF.png?v=1773598289"},{"product_id":"met-antibody-sc-f0288","title":"Met Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eThe Met tyrosine kinase, encoded by the c-met proto-oncogene, acts as the high-affinity receptor for hepatocyte growth factor (HGF). Comprising a 50-kDa α-subunit and a 145-kDa β-subunit, linked by a disulfide bond, Met plays crucial roles in both embryo development and tumor invasion. HGF, existing as a mature α\/β heterodimer, contains a high-affinity Met-binding site in the α-chain (HGF-α) and a low-affinity Met-binding site in the β-chain (HGF-β). Depending on the literature source, MET may also be discussed as c-Met.\u003c\/p\u003e\u003cp\u003eReported cellular context includes membrane and secreted, which can matter when signal is compared across treatments or changing cell states. Following MET 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\u003eMET 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 membrane and secreted, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between membrane and secreted 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 MET. 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 MET reflect biology rather than handling. When interpreting MET, 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 MET 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":57577438052697,"sku":"F0288-20UL","price":169.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577438085465,"sku":"F0288-100UL","price":379.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577438118233,"sku":"F0288-2X100UL","price":569.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0288-IHC1.jpg?v=1773598294"},{"product_id":"pik3ca-antibody-sc-f0293","title":"PI3 Kinase p110α Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003ePI3 Kinase p110α (Phosphoinositide 3-kinase p110α, PI3K p110α), encoded by the PIK3CA gene, is a catalytic subunit of class I PI3Ks that plays a central role in cell signaling downstream of receptor tyrosine kinases (RTKs), small GTPases like Ras, and G-protein βγ subunits. Structurally, p110α consists of multiple domains, including the adaptor-binding domain (ABD), Ras-binding domain (RBD), C2 domain, helical domain, and the kinase domain, and forms a heterodimer with a regulatory subunit (e. g., p85α), which contains SH2 domains critical for recruitment to phosphotyrosine residues. Depending on the literature source, PIK3CA may also be discussed as PI3 Kinase p110alpha and Phosphatidylinositol 4.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm, cytosol, and plasma membrane, which can matter when signal is compared across treatments or changing cell states. Following PIK3CA 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\u003ePIK3CA 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, cytosol, and plasma 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, cytosol, and plasma membrane 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 PIK3CA. 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 PIK3CA reflect biology rather than handling. When interpreting PIK3CA, 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 PIK3CA 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":57577438347609,"sku":"F0293-20UL","price":199.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577438380377,"sku":"F0293-100UL","price":489.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577438413145,"sku":"F0293-2X100UL","price":729.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0293-wb.gif?v=1773598297"},{"product_id":"ctnnb1-antibody-sc-f0297","title":"Phospho-β-Catenin (Ser675) Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eCTNNB1 is a target of interest in many antibody-based workflows. β-catenin serves as an essential structural element within cadherin-based adherens junctions and acts as the principal nuclear effector of canonical Wnt signaling. In this cascade, β-catenin transduces the signal to the nucleus, initiating the transcription of Wnt-specific genes that regulate cell fate decisions across various cells and tissues. Depending on the literature source, CTNNB1 may also be discussed as Phospho-beta-Catenin (Ser675).\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell junction, cell membrane, cell projection, and cytoplasm, which can matter when signal is compared across treatments or changing cell states. Following CTNNB1 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\u003eCTNNB1 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 cell projection, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cell junction, cell membrane, and cell projection 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 CTNNB1. 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 CTNNB1 reflect biology rather than handling. When interpreting CTNNB1, 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 CTNNB1 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":57577438740825,"sku":"F0297-20UL","price":169.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577438773593,"sku":"F0297-100UL","price":419.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577438806361,"sku":"F0297-2X100UL","price":629.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0297-wb.gif?v=1773598303"},{"product_id":"egfr-antibody-sc-f0298","title":"Phospho-EGF Receptor (Tyr1068) Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eThe epidermal growth factor receptor (EGFR) is a transmembrane tyrosine kinase that is part of the HER\/ErbB protein family. Upon ligand binding, the receptor undergoes dimerization, autophosphorylation, activation of downstream signaling pathways, internalization, and degradation in lysosomes. Phosphorylation of EGFR at Tyr845 within the kinase domain plays a crucial role in stabilizing the activation loop, maintaining the enzyme in its active state, and providing a binding site for substrate proteins. c-Src kinase is involved in the phosphorylation of Tyr845 on EGFR. Depending on the literature source, EGFR may also be discussed as Phospho-EGF Receptor (Tyr1068) and Phospho EGFR (Tyr1068).\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 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\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 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":57577438839129,"sku":"F0298-20UL","price":169.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577438871897,"sku":"F0298-100UL","price":429.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577438904665,"sku":"F0298-2X100UL","price":639.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0298-IHC1.jpg?v=1773598306"},{"product_id":"rb-antibody-sc-f0302","title":"Phospho-Rb (Ser807\/811) Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eThe retinoblastoma (RB) tumor suppressor regulates cell cycle progression by interacting with E2F transcription factors. Binding of RB to E2F at gene promoters crucial for S phase progression inhibits transcription by preventing co-activator recruitment or promoting co-repressor recruitment. Mitogen-induced activation of cyclin-dependent kinases (CDK4, CDK6, and CDK2) phosphorylates RB, relieving its inhibition on cell cycle transition from G1 to S phase. Depending on the literature source, RB may also be discussed as Phospho-Rb (Ser807\/811).\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 RB 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\u003eRB 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 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\u003ecell-cycle linked differences in abundance, timing, or compartmental enrichment\u003c\/li\u003e\n\u003cli\u003edifferences between total target abundance and site-specific regulation when modified forms are compared\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for RB. 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 RB reflect biology rather than handling. When interpreting RB, 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 RB 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":57577439166809,"sku":"F0302-20UL","price":169.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577439199577,"sku":"F0302-100UL","price":429.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577439232345,"sku":"F0302-2X100UL","price":639.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0302-IHC1.jpg?v=1773598309"},{"product_id":"src-family-antibody-sc-f0304","title":"Phospho-Src Family (Tyr416) Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eThe Src family of protein tyrosine kinases, which includes Src, Lyn, Fyn, Yes, Lck, Blk, and Hck, plays a crucial role in regulating the growth and differentiation of eukaryotic cells. Src is activated by a wide range of extracellular signals, including integrins, G-protein-coupled receptors, steroid receptors, and receptor tyrosine kinases (RTKs) such as platelet-derived growth factor receptor (PDGFR), the epidermal growth factor receptor (EGFR) family, fibroblast growth factor receptor (FGFR), insulin-like growth factor-1 receptor (IGF-1R), c-Met, colony-stimulating factor-1 receptor (CSF-1R), and stem cell factor receptor (SCFR), among others. Depending on the literature source, SRC family may also be discussed as Phospho-Src Family (Tyr416) and YES.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell membrane, cytoplasm, cytoskeleton, and membrane, which can matter when signal is compared across treatments or changing cell states. Following SRC family 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\u003eSRC family 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 cell membrane, 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 cell membrane, cytoplasm, and cytoskeleton 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 SRC family. 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 SRC family reflect biology rather than handling. When interpreting SRC family, 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 SRC family 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":57577439953241,"sku":"F0304-20UL","price":159.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577439986009,"sku":"F0304-100UL","price":389.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577440018777,"sku":"F0304-2X100UL","price":579.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0304-wb.gif?v=1773598310"},{"product_id":"suz12-antibody-sc-f0307","title":"SUZ12 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eSUZ12 is a target of interest in many antibody-based workflows. The polycomb group (PcG) proteins play a crucial role in maintaining cell identity, regulating stem cell self-renewal, controlling the cell cycle, and contributing to oncogenesis. They achieve this by keeping certain genes silenced, which are involved in cell lineage specification, cell death, and cell cycle arrest.\u003c\/p\u003e\u003cp\u003eReported cellular context includes nucleus, which can matter when signal is compared across treatments or changing cell states. Following SUZ12 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\u003eSUZ12 is commonly interpreted in the context of cancer, stem cell 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\u003echanges associated with proliferative state, oncogenic signaling, or treatment response\u003c\/li\u003e\n\u003cli\u003estate transitions between self-renewal, priming, and differentiation\u003c\/li\u003e\n\u003cli\u003elinks between target behavior and transcriptional or chromatin-state changes\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for SUZ12. 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 SUZ12 reflect biology rather than handling. When interpreting SUZ12, 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 SUZ12 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":57577440280921,"sku":"F0307-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577440313689,"sku":"F0307-100UL","price":359.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577440346457,"sku":"F0307-2X100UL","price":539.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0307-IF.png?v=1773598316"},{"product_id":"tsc2-antibody-sc-f0311","title":"Tuberin\/TSC2 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eTuberous sclerosis complex (TSC) is a syndrome caused by mutations in either the TSC1 or TSC2 tumor suppressor genes. It is characterized by seizures, mental retardation, autism, and the development of tumors in various organs, including the brain, kidney, heart, retina, and skin. TSC2 encodes a protein called tuberin, which plays a critical role in regulating cell proliferation and tumor formation. Depending on the literature source, TSC2 may also be discussed as Tuberin\/TSC2 and Tuberin.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm, lysosome, and membrane, which can matter when signal is compared across treatments or changing cell states. Following TSC2 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\u003eTSC2 is commonly interpreted in the context of cancer, neuroscience, and endocrinology research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cytoplasm, lysosome, 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, lysosome, 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 to hormone-dependent signaling or endocrine feedback context\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 TSC2. 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 TSC2 reflect biology rather than handling. When interpreting TSC2, 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 TSC2 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":57577440674137,"sku":"F0311-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577440706905,"sku":"F0311-100UL","price":359.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577440739673,"sku":"F0311-2X100UL","price":539.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0311-IF.png?v=1773598321"},{"product_id":"ptgs2-antibody-sc-f0327","title":"COX2 \/ Cyclooxygenase 2 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003ePTGS2 is a target of interest in many antibody-based workflows. COX-1 and COX-2 are isoenzymes. COX-2 expression is rapidly induced by various stimuli such as proinflammatory cytokines, lipopolysaccharides, mitogens, oncogenes, growth factors, hormones, and disorders of water-electrolyte hemostasis. This induction leads to increased synthesis of prostaglandins in inflamed and neoplastic tissues. Depending on the literature source, PTGS2 may also be discussed as COX2 \/ Cyclooxygenase 2 and Prostaglandin G\/H synthase 2.\u003c\/p\u003e\u003cp\u003eReported cellular context includes endoplasmic reticulum, membrane, microsome, and nucleus, which can matter when signal is compared across treatments or changing cell states. Following PTGS2 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\u003ePTGS2 is commonly interpreted in the context of cancer, immunology, and inflammation research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans endoplasmic reticulum, membrane, and microsome, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between endoplasmic reticulum, membrane, and microsome across matched conditions\u003c\/li\u003e\n\u003cli\u003echanges associated with proliferative state, oncogenic signaling, or treatment response\u003c\/li\u003e\n\u003cli\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\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 PTGS2. 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 PTGS2 reflect biology rather than handling. When interpreting PTGS2, 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 PTGS2 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":57577443688793,"sku":"F0327-20UL","price":159.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577443721561,"sku":"F0327-100UL","price":359.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577443754329,"sku":"F0327-2X100UL","price":539.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0327-IF.png?v=1773598344"},{"product_id":"map2k1-map2k2-antibody-sc-f0334","title":"MEK1\/2 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eMEK1\/2 is a target of interest in many antibody-based workflows. MEK1 and MEK2, are dual-specificity protein kinases also known as MAPK or Erk kinases, involved in a mitogen-activated protein kinase cascade regulating cell growth and differentiation. MEK1's structure, denoted for MAP kinase or ERK kinase, was elucidated from a complementary DNA sequence. Depending on the literature source, MEK1\/2 may also be discussed as MEK1\/2 and MAPKK 1.\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 MEK1\/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\u003eMEK1\/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 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\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 MEK1\/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 MEK1\/2 reflect biology rather than handling. When interpreting MEK1\/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 MEK1\/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":57577444180313,"sku":"F0334-20UL","price":139.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577444213081,"sku":"F0334-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577444245849,"sku":"F0334-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0334-IF.png?v=1773598353"},{"product_id":"ctnnb1-antibody-sc-f0336","title":"Non-phospho β-Catenin (S33\/37\/T41) Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eCTNNB1 is a target of interest in many antibody-based workflows. β-catenin, initially recognized as a cell-cell adhesion protein, functions as a crucial downstream effector in the Wnt signaling pathway, also participating in signal transduction in developmental systems. GSK-3β destabilizes β-catenin by phosphorylating it at Ser 33, Ser 37, and Thr 41. Mutations at these sites result in the stabilization of β-catenin protein levels and have been found in many tumor cell lines. Depending on the literature source, CTNNB1 may also be discussed as Non-phospho beta-Catenin (S33\/37\/T41).\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell junction, cell membrane, cell projection, and cytoplasm, which can matter when signal is compared across treatments or changing cell states. Following CTNNB1 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\u003eCTNNB1 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 cell projection, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cell junction, cell membrane, and cell projection 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 CTNNB1. 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 CTNNB1 reflect biology rather than handling. When interpreting CTNNB1, 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 CTNNB1 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":57577444442457,"sku":"F0336-20UL","price":159.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577444475225,"sku":"F0336-100UL","price":389.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577444507993,"sku":"F0336-2X100UL","price":579.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0336-IHC1.jpg?v=1773598356"},{"product_id":"eif4ebp1-antibody-sc-f0339","title":"Phospho-4E-BP1 (Ser65) Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eEIF4EBP1 is a target of interest in many antibody-based workflows. Phospho-4E-BP1 (Ser65) is an essential regulator of cap-dependent translation initiation, primarily modulated by the mTOR signaling pathway. This phosphorylation facilitates the release of 4E-BP1 from eIF4E, allowing for the formation of the eIF4F complex required for protein synthesis. As a significant biomarker, its phosphorylation status reflects mTOR activity and provides insights into the translational control mechanisms responding to growth factors and nutrient levels. Depending on the literature source, EIF4EBP1 may also be discussed as Phospho-4E-BP1 (Ser65) and p-4E-BP1.\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 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\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 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":57577445130585,"sku":"F0339-20UL","price":169.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577445163353,"sku":"F0339-100UL","price":389.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577445196121,"sku":"F0339-2X100UL","price":579.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0339-wb.gif?v=1773598357"},{"product_id":"map2k1-map2k2-antibody-sc-f0345","title":"Phospho-MEK1\/2 (Ser217\/221) Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003ePhospho-MEK1\/2 (Ser217\/221) is a target of interest in many antibody-based workflows. MEK1 and MEK2, also known as MAPK or Erk kinases, are dual-specificity protein kinases involved in a mitogen-activated protein kinase cascade that regulates cell growth and differentiation. Activation of MEK1 and MEK2 involves phosphorylation of two serine residues (at positions 217 and 221) located in the activation loop of subdomain VIII by Raf-like molecules. Depending on the literature source, Phospho-MEK1\/2 (Ser217\/221) may also be discussed as Phospho-MEK1\/2 (Ser217\/221) and Phospho MEK1 (Ser 217).\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm, membrane, nucleus, and cytoskeleton, which can matter when signal is compared across treatments or changing cell states. Following Phospho-MEK1\/2 (Ser217\/221) 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-MEK1\/2 (Ser217\/221) 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 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\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-MEK1\/2 (Ser217\/221). 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-MEK1\/2 (Ser217\/221) reflect biology rather than handling. When interpreting Phospho-MEK1\/2 (Ser217\/221), 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-MEK1\/2 (Ser217\/221) 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":57577445327193,"sku":"F0345-20UL","price":159.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577445359961,"sku":"F0345-100UL","price":389.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577445392729,"sku":"F0345-2X100UL","price":579.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0345-wb.gif?v=1773598360"}],"url":"https:\/\/absource.de\/collections\/oncology.oembed?page=286","provider":"Absource Diagnostics","version":"1.0","type":"link"}