ap 1 transcription factor subunit Search Results


92
MedChemExpress kinases jun transcription factor ap 1 junb junb proto oncogene kegg kyoto encyclopedia
Kinases Jun Transcription Factor Ap 1 Junb Junb Proto Oncogene Kegg Kyoto Encyclopedia, supplied by MedChemExpress, used in various techniques. Bioz Stars score: 92/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Proteintech jun antibody
Jun Antibody, supplied by Proteintech, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Proteintech anti phospho jun
Anti Phospho Jun, supplied by Proteintech, used in various techniques. Bioz Stars score: 93/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Boster Bio rabbit anti jun
Rabbit Anti Jun, supplied by Boster Bio, used in various techniques. Bioz Stars score: 93/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Proteintech 10024 2 ap
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Proteintech junb
Identification of TIRS regulatory mechanisms and key biomarkers. A LASSO-based feature selection, with the optimal lambda determined when the partial likelihood deviance reached the minimum value (left). SVM-RFE-based feature selection, with root mean square error (RMSE) reached the minimum value and R -squared reached the max value (mid). Venn diagram presented the intersection of key biomarkers obtained through both algorithms (right). B Aberrant expression profiles for key biomarkers in Abdominal Aortic Wall Dataset 1 (AAA n = 80 patients, control n = 10 healthy individuals; Student’s t -test). C ROC curve demonstrating the diagnostic efficacy <t>of</t> <t>FOSB,</t> <t>JUNB,</t> CST7, and TBC1D4 in Abdominal Aortic Wall Dataset 1. D Clinical impact plot illustrating the clinical utility of key biomarkers. The “Number high risk” curve closely aligns with the “Number high risk with the event” curve at each threshold probability, indicating exceptional predictive power. E Aberrant expression profiles for key biomarkers in Abdominal Aortic Wall Dataset 2 (AAA n = 9 patients, control n = 10 healthy individuals; Student’s t -test). F ROC curve validating the diagnostic efficacy of FOSB, JUNB, CST7, and TBC1D4 in Abdominal Aortic Wall Dataset 2. G Clinical impact plot demonstrating the clinical utility of key biomarkers. Again, the “Number high risk” curve is closely aligned with the “Number high risk with the event” curve at each threshold probability, highlighting the biomarkers’ strong predictive power. H Aberrant expression profiles for key biomarkers in Perivascular Adipose Tissue Dataset 3 (dilated n = 30, non-dilated n = 30; Student’s t -test). I ROC curve verifying the diagnostic efficacy of FOSB, JUNB, CST7, and TBC1D4 in Perivascular Adipose Tissue Dataset 3. J Impact plots reiterated superior predictive performance probability, indicating outstanding predictive capability
Junb, supplied by Proteintech, used in various techniques. Bioz Stars score: 93/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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90
Active Motif activator protein-1 (ap-1) activity elisa kit transamtm ap-1-c-jun
Identification of TIRS regulatory mechanisms and key biomarkers. A LASSO-based feature selection, with the optimal lambda determined when the partial likelihood deviance reached the minimum value (left). SVM-RFE-based feature selection, with root mean square error (RMSE) reached the minimum value and R -squared reached the max value (mid). Venn diagram presented the intersection of key biomarkers obtained through both algorithms (right). B Aberrant expression profiles for key biomarkers in Abdominal Aortic Wall Dataset 1 (AAA n = 80 patients, control n = 10 healthy individuals; Student’s t -test). C ROC curve demonstrating the diagnostic efficacy <t>of</t> <t>FOSB,</t> <t>JUNB,</t> CST7, and TBC1D4 in Abdominal Aortic Wall Dataset 1. D Clinical impact plot illustrating the clinical utility of key biomarkers. The “Number high risk” curve closely aligns with the “Number high risk with the event” curve at each threshold probability, indicating exceptional predictive power. E Aberrant expression profiles for key biomarkers in Abdominal Aortic Wall Dataset 2 (AAA n = 9 patients, control n = 10 healthy individuals; Student’s t -test). F ROC curve validating the diagnostic efficacy of FOSB, JUNB, CST7, and TBC1D4 in Abdominal Aortic Wall Dataset 2. G Clinical impact plot demonstrating the clinical utility of key biomarkers. Again, the “Number high risk” curve is closely aligned with the “Number high risk with the event” curve at each threshold probability, highlighting the biomarkers’ strong predictive power. H Aberrant expression profiles for key biomarkers in Perivascular Adipose Tissue Dataset 3 (dilated n = 30, non-dilated n = 30; Student’s t -test). I ROC curve verifying the diagnostic efficacy of FOSB, JUNB, CST7, and TBC1D4 in Perivascular Adipose Tissue Dataset 3. J Impact plots reiterated superior predictive performance probability, indicating outstanding predictive capability
Activator Protein 1 (Ap 1) Activity Elisa Kit Transamtm Ap 1 C Jun, supplied by Active Motif, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Sanyal Biotechnology elevated creb- and ap1-dependent transcription
Identification of TIRS regulatory mechanisms and key biomarkers. A LASSO-based feature selection, with the optimal lambda determined when the partial likelihood deviance reached the minimum value (left). SVM-RFE-based feature selection, with root mean square error (RMSE) reached the minimum value and R -squared reached the max value (mid). Venn diagram presented the intersection of key biomarkers obtained through both algorithms (right). B Aberrant expression profiles for key biomarkers in Abdominal Aortic Wall Dataset 1 (AAA n = 80 patients, control n = 10 healthy individuals; Student’s t -test). C ROC curve demonstrating the diagnostic efficacy <t>of</t> <t>FOSB,</t> <t>JUNB,</t> CST7, and TBC1D4 in Abdominal Aortic Wall Dataset 1. D Clinical impact plot illustrating the clinical utility of key biomarkers. The “Number high risk” curve closely aligns with the “Number high risk with the event” curve at each threshold probability, indicating exceptional predictive power. E Aberrant expression profiles for key biomarkers in Abdominal Aortic Wall Dataset 2 (AAA n = 9 patients, control n = 10 healthy individuals; Student’s t -test). F ROC curve validating the diagnostic efficacy of FOSB, JUNB, CST7, and TBC1D4 in Abdominal Aortic Wall Dataset 2. G Clinical impact plot demonstrating the clinical utility of key biomarkers. Again, the “Number high risk” curve is closely aligned with the “Number high risk with the event” curve at each threshold probability, highlighting the biomarkers’ strong predictive power. H Aberrant expression profiles for key biomarkers in Perivascular Adipose Tissue Dataset 3 (dilated n = 30, non-dilated n = 30; Student’s t -test). I ROC curve verifying the diagnostic efficacy of FOSB, JUNB, CST7, and TBC1D4 in Perivascular Adipose Tissue Dataset 3. J Impact plots reiterated superior predictive performance probability, indicating outstanding predictive capability
Elevated Creb And Ap1 Dependent Transcription, supplied by Sanyal Biotechnology, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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DWK Life Sciences ap-1 transcription factor
Identification of TIRS regulatory mechanisms and key biomarkers. A LASSO-based feature selection, with the optimal lambda determined when the partial likelihood deviance reached the minimum value (left). SVM-RFE-based feature selection, with root mean square error (RMSE) reached the minimum value and R -squared reached the max value (mid). Venn diagram presented the intersection of key biomarkers obtained through both algorithms (right). B Aberrant expression profiles for key biomarkers in Abdominal Aortic Wall Dataset 1 (AAA n = 80 patients, control n = 10 healthy individuals; Student’s t -test). C ROC curve demonstrating the diagnostic efficacy <t>of</t> <t>FOSB,</t> <t>JUNB,</t> CST7, and TBC1D4 in Abdominal Aortic Wall Dataset 1. D Clinical impact plot illustrating the clinical utility of key biomarkers. The “Number high risk” curve closely aligns with the “Number high risk with the event” curve at each threshold probability, indicating exceptional predictive power. E Aberrant expression profiles for key biomarkers in Abdominal Aortic Wall Dataset 2 (AAA n = 9 patients, control n = 10 healthy individuals; Student’s t -test). F ROC curve validating the diagnostic efficacy of FOSB, JUNB, CST7, and TBC1D4 in Abdominal Aortic Wall Dataset 2. G Clinical impact plot demonstrating the clinical utility of key biomarkers. Again, the “Number high risk” curve is closely aligned with the “Number high risk with the event” curve at each threshold probability, highlighting the biomarkers’ strong predictive power. H Aberrant expression profiles for key biomarkers in Perivascular Adipose Tissue Dataset 3 (dilated n = 30, non-dilated n = 30; Student’s t -test). I ROC curve verifying the diagnostic efficacy of FOSB, JUNB, CST7, and TBC1D4 in Perivascular Adipose Tissue Dataset 3. J Impact plots reiterated superior predictive performance probability, indicating outstanding predictive capability
Ap 1 Transcription Factor, supplied by DWK Life Sciences, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Active Motif activated proteins-1 (ap-1) transcription factor elisa kit
Identification of TIRS regulatory mechanisms and key biomarkers. A LASSO-based feature selection, with the optimal lambda determined when the partial likelihood deviance reached the minimum value (left). SVM-RFE-based feature selection, with root mean square error (RMSE) reached the minimum value and R -squared reached the max value (mid). Venn diagram presented the intersection of key biomarkers obtained through both algorithms (right). B Aberrant expression profiles for key biomarkers in Abdominal Aortic Wall Dataset 1 (AAA n = 80 patients, control n = 10 healthy individuals; Student’s t -test). C ROC curve demonstrating the diagnostic efficacy <t>of</t> <t>FOSB,</t> <t>JUNB,</t> CST7, and TBC1D4 in Abdominal Aortic Wall Dataset 1. D Clinical impact plot illustrating the clinical utility of key biomarkers. The “Number high risk” curve closely aligns with the “Number high risk with the event” curve at each threshold probability, indicating exceptional predictive power. E Aberrant expression profiles for key biomarkers in Abdominal Aortic Wall Dataset 2 (AAA n = 9 patients, control n = 10 healthy individuals; Student’s t -test). F ROC curve validating the diagnostic efficacy of FOSB, JUNB, CST7, and TBC1D4 in Abdominal Aortic Wall Dataset 2. G Clinical impact plot demonstrating the clinical utility of key biomarkers. Again, the “Number high risk” curve is closely aligned with the “Number high risk with the event” curve at each threshold probability, highlighting the biomarkers’ strong predictive power. H Aberrant expression profiles for key biomarkers in Perivascular Adipose Tissue Dataset 3 (dilated n = 30, non-dilated n = 30; Student’s t -test). I ROC curve verifying the diagnostic efficacy of FOSB, JUNB, CST7, and TBC1D4 in Perivascular Adipose Tissue Dataset 3. J Impact plots reiterated superior predictive performance probability, indicating outstanding predictive capability
Activated Proteins 1 (Ap 1) Transcription Factor Elisa Kit, supplied by Active Motif, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Promega double-stranded oligonucleotides containing the canonical dna-binding sites for transcription factors ap-1, nf-kb, sp1, and ap-2
Identification of TIRS regulatory mechanisms and key biomarkers. A LASSO-based feature selection, with the optimal lambda determined when the partial likelihood deviance reached the minimum value (left). SVM-RFE-based feature selection, with root mean square error (RMSE) reached the minimum value and R -squared reached the max value (mid). Venn diagram presented the intersection of key biomarkers obtained through both algorithms (right). B Aberrant expression profiles for key biomarkers in Abdominal Aortic Wall Dataset 1 (AAA n = 80 patients, control n = 10 healthy individuals; Student’s t -test). C ROC curve demonstrating the diagnostic efficacy <t>of</t> <t>FOSB,</t> <t>JUNB,</t> CST7, and TBC1D4 in Abdominal Aortic Wall Dataset 1. D Clinical impact plot illustrating the clinical utility of key biomarkers. The “Number high risk” curve closely aligns with the “Number high risk with the event” curve at each threshold probability, indicating exceptional predictive power. E Aberrant expression profiles for key biomarkers in Abdominal Aortic Wall Dataset 2 (AAA n = 9 patients, control n = 10 healthy individuals; Student’s t -test). F ROC curve validating the diagnostic efficacy of FOSB, JUNB, CST7, and TBC1D4 in Abdominal Aortic Wall Dataset 2. G Clinical impact plot demonstrating the clinical utility of key biomarkers. Again, the “Number high risk” curve is closely aligned with the “Number high risk with the event” curve at each threshold probability, highlighting the biomarkers’ strong predictive power. H Aberrant expression profiles for key biomarkers in Perivascular Adipose Tissue Dataset 3 (dilated n = 30, non-dilated n = 30; Student’s t -test). I ROC curve verifying the diagnostic efficacy of FOSB, JUNB, CST7, and TBC1D4 in Perivascular Adipose Tissue Dataset 3. J Impact plots reiterated superior predictive performance probability, indicating outstanding predictive capability
Double Stranded Oligonucleotides Containing The Canonical Dna Binding Sites For Transcription Factors Ap 1, Nf Kb, Sp1, And Ap 2, supplied by Promega, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Image Search Results


Identification of TIRS regulatory mechanisms and key biomarkers. A LASSO-based feature selection, with the optimal lambda determined when the partial likelihood deviance reached the minimum value (left). SVM-RFE-based feature selection, with root mean square error (RMSE) reached the minimum value and R -squared reached the max value (mid). Venn diagram presented the intersection of key biomarkers obtained through both algorithms (right). B Aberrant expression profiles for key biomarkers in Abdominal Aortic Wall Dataset 1 (AAA n = 80 patients, control n = 10 healthy individuals; Student’s t -test). C ROC curve demonstrating the diagnostic efficacy of FOSB, JUNB, CST7, and TBC1D4 in Abdominal Aortic Wall Dataset 1. D Clinical impact plot illustrating the clinical utility of key biomarkers. The “Number high risk” curve closely aligns with the “Number high risk with the event” curve at each threshold probability, indicating exceptional predictive power. E Aberrant expression profiles for key biomarkers in Abdominal Aortic Wall Dataset 2 (AAA n = 9 patients, control n = 10 healthy individuals; Student’s t -test). F ROC curve validating the diagnostic efficacy of FOSB, JUNB, CST7, and TBC1D4 in Abdominal Aortic Wall Dataset 2. G Clinical impact plot demonstrating the clinical utility of key biomarkers. Again, the “Number high risk” curve is closely aligned with the “Number high risk with the event” curve at each threshold probability, highlighting the biomarkers’ strong predictive power. H Aberrant expression profiles for key biomarkers in Perivascular Adipose Tissue Dataset 3 (dilated n = 30, non-dilated n = 30; Student’s t -test). I ROC curve verifying the diagnostic efficacy of FOSB, JUNB, CST7, and TBC1D4 in Perivascular Adipose Tissue Dataset 3. J Impact plots reiterated superior predictive performance probability, indicating outstanding predictive capability

Journal: BMC Biology

Article Title: Machine learning combined with omics-based approaches reveals T-lymphocyte cellular fate imbalance in abdominal aortic aneurysm

doi: 10.1186/s12915-025-02400-x

Figure Lengend Snippet: Identification of TIRS regulatory mechanisms and key biomarkers. A LASSO-based feature selection, with the optimal lambda determined when the partial likelihood deviance reached the minimum value (left). SVM-RFE-based feature selection, with root mean square error (RMSE) reached the minimum value and R -squared reached the max value (mid). Venn diagram presented the intersection of key biomarkers obtained through both algorithms (right). B Aberrant expression profiles for key biomarkers in Abdominal Aortic Wall Dataset 1 (AAA n = 80 patients, control n = 10 healthy individuals; Student’s t -test). C ROC curve demonstrating the diagnostic efficacy of FOSB, JUNB, CST7, and TBC1D4 in Abdominal Aortic Wall Dataset 1. D Clinical impact plot illustrating the clinical utility of key biomarkers. The “Number high risk” curve closely aligns with the “Number high risk with the event” curve at each threshold probability, indicating exceptional predictive power. E Aberrant expression profiles for key biomarkers in Abdominal Aortic Wall Dataset 2 (AAA n = 9 patients, control n = 10 healthy individuals; Student’s t -test). F ROC curve validating the diagnostic efficacy of FOSB, JUNB, CST7, and TBC1D4 in Abdominal Aortic Wall Dataset 2. G Clinical impact plot demonstrating the clinical utility of key biomarkers. Again, the “Number high risk” curve is closely aligned with the “Number high risk with the event” curve at each threshold probability, highlighting the biomarkers’ strong predictive power. H Aberrant expression profiles for key biomarkers in Perivascular Adipose Tissue Dataset 3 (dilated n = 30, non-dilated n = 30; Student’s t -test). I ROC curve verifying the diagnostic efficacy of FOSB, JUNB, CST7, and TBC1D4 in Perivascular Adipose Tissue Dataset 3. J Impact plots reiterated superior predictive performance probability, indicating outstanding predictive capability

Article Snippet: The primary antibodies against FOSB (1:500, catalog No. ab184938, Abcam) and JUNB (1:50, catalog No. 10486–1-AP, Proteintech) were incubated overnight at 4 °C, followed by incubation with horseradish peroxidase conjugated secondary antibodies.

Techniques: Selection, Expressing, Control, Diagnostic Assay

Verification of key biomarkers. A Abdominal aortic wall and peripheral blood samples obtained from AAA patients. B Aberrant expression profiles for key biomarkers in the abdominal aortic wall (Inhouse Dataset 1; AAA n = 5 patients, control n = 4 healthy individuals). C ROC curve validating the diagnostic efficacy of FOSB, JUNB, CST7, and TBC1D4 in the abdominal aortic wall (Inhouse Dataset 1). D Clinical impact plot demonstrating the clinical utility of key biomarkers. The “Number high risk” curve closely aligns with the “Number high risk with the event” curve at each threshold probability, indicating exceptional predictive power. E Aberrant expression profiles for key biomarkers in peripheral blood (Inhouse Dataset 2; AAA n = 24 patients, control n = 15 healthy individuals). F ROC curve validating the diagnostic efficacy of FOSB, JUNB, CST7, and TBC1D4 in peripheral blood (Inhouse Dataset 2). G Clinical impact plot illustrating the clinical utility of key biomarkers. Again, the “Number high risk” curve remains closely aligned with the “Number high risk with the event” curve at each threshold probability, highlighting the biomarkers’ strong predictive capability. H Mice were infused with saline or Ang II (1000 ng/kg/min) + BAPN. Gross abdominal aorta images were shown. Scale bar is 1 cm. I Representative images of immunohistochemical stains for elastin fiber (Van Gieson) and representative photomicrographs of hematoxylin and eosin (H&E) staining. Scale bar is 200 μm. J – L Representative immunohistochemical staining of FOSB and JUNB in aortic cross sections. Scale bar is 50 μm. Data are expressed as mean ± SEM (control n = 3 mice, AAA n = 5 or 6 mice). Student’s t -test was utilized to compare continuous variables between the two groups

Journal: BMC Biology

Article Title: Machine learning combined with omics-based approaches reveals T-lymphocyte cellular fate imbalance in abdominal aortic aneurysm

doi: 10.1186/s12915-025-02400-x

Figure Lengend Snippet: Verification of key biomarkers. A Abdominal aortic wall and peripheral blood samples obtained from AAA patients. B Aberrant expression profiles for key biomarkers in the abdominal aortic wall (Inhouse Dataset 1; AAA n = 5 patients, control n = 4 healthy individuals). C ROC curve validating the diagnostic efficacy of FOSB, JUNB, CST7, and TBC1D4 in the abdominal aortic wall (Inhouse Dataset 1). D Clinical impact plot demonstrating the clinical utility of key biomarkers. The “Number high risk” curve closely aligns with the “Number high risk with the event” curve at each threshold probability, indicating exceptional predictive power. E Aberrant expression profiles for key biomarkers in peripheral blood (Inhouse Dataset 2; AAA n = 24 patients, control n = 15 healthy individuals). F ROC curve validating the diagnostic efficacy of FOSB, JUNB, CST7, and TBC1D4 in peripheral blood (Inhouse Dataset 2). G Clinical impact plot illustrating the clinical utility of key biomarkers. Again, the “Number high risk” curve remains closely aligned with the “Number high risk with the event” curve at each threshold probability, highlighting the biomarkers’ strong predictive capability. H Mice were infused with saline or Ang II (1000 ng/kg/min) + BAPN. Gross abdominal aorta images were shown. Scale bar is 1 cm. I Representative images of immunohistochemical stains for elastin fiber (Van Gieson) and representative photomicrographs of hematoxylin and eosin (H&E) staining. Scale bar is 200 μm. J – L Representative immunohistochemical staining of FOSB and JUNB in aortic cross sections. Scale bar is 50 μm. Data are expressed as mean ± SEM (control n = 3 mice, AAA n = 5 or 6 mice). Student’s t -test was utilized to compare continuous variables between the two groups

Article Snippet: The primary antibodies against FOSB (1:500, catalog No. ab184938, Abcam) and JUNB (1:50, catalog No. 10486–1-AP, Proteintech) were incubated overnight at 4 °C, followed by incubation with horseradish peroxidase conjugated secondary antibodies.

Techniques: Expressing, Control, Diagnostic Assay, Saline, Immunohistochemical staining, Staining