AIMC Topic: Poly-ADP-Ribose Binding Proteins

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Differential gene expression analysis and machine learning identified structural, TFs, cytokine and glycoproteins, including SOX2, TOP2A, SPP1, COL1A1, and TIMP1 as potential drivers of lung cancer.

Biomarkers : biochemical indicators of exposure, response, and susceptibility to chemicals Feb 10, 2025
BACKGROUND: Lung cancer is a primary global health concern, responsible for a considerable portion of cancer-related fatalities worldwide. Understanding its molecular complexities is crucial for identifying potential targets for treatment. The goal i...
Osteopontin Collagen Type I Lung Neoplasms Biomarkers, Tumor Gene Expression Regulation, Neoplastic Gene Expression Profiling Poly-ADP-Ribose Binding Proteins Protein Interaction Maps Collagen Type I, alpha 1 Chain Gene Regulatory Networks DNA Topoisomerases, Type II Humans Tissue Inhibitor of Metalloproteinase-1 Machine Learning SOXB1 Transcription Factors
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Deep learning based analysis of G3BP1 protein expression to predict the prognosis of nasopharyngeal carcinoma.

PloS one Jan 27, 2025
BACKGROUND: Ras-GTPase-activating protein (GAP)-binding protein 1 (G3BP1) emerges as a pivotal oncogenic gene across various malignancies, notably including nasopharyngeal carcinoma (NPC). The use of automated image analysis tools for immunohistochem...
Gene Expression Regulation, Neoplastic DNA Helicases Middle Aged Deep Learning Nasopharyngeal Neoplasms Poly-ADP-Ribose Binding Proteins Immunohistochemistry Nasopharyngeal Carcinoma Female Adult Biomarkers, Tumor Male Humans Prognosis RNA Recognition Motif Proteins RNA Helicases
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Machine learning-based prediction of microsatellite instability and high tumor mutation burden from contrast-enhanced computed tomography in endometrial cancers.

Scientific reports Oct 20, 2020
To evaluate whether radiomic features from contrast-enhanced computed tomography (CE-CT) can identify DNA mismatch repair deficient (MMR-D) and/or tumor mutational burden-high (TMB-H) endometrial cancers (ECs). Patients who underwent targeted massive...
DNA Polymerase II Poly-ADP-Ribose Binding Proteins Tomography, X-Ray Computed Female Aged Middle Aged Computer Simulation Prognosis Humans DNA Mismatch Repair Neoplasm Staging Machine Learning Mutation Microsatellite Instability Endometrial Neoplasms Cohort Studies Tumor Suppressor Protein p53 Carcinoma, Endometrioid Uterus
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Integrative PPI network and random forest analysis identifies KIF4A, TOP2A, and ASPM protein macromolecules as novel protein biomarkers in renal carcinoma pathogenesis.

International journal of biological macromolecules Jun 1, 2025
The pathogenesis of kidney cancer is not fully understood, so there is an urgent need to identify new biomarkers to improve diagnosis and treatment. The study identified KIF4A, TOP2A and ASPM as novel protein biomarkers for renal cancer and explored ...
Random Forest Kidney Neoplasms Nerve Tissue Proteins Cell Line, Tumor Epithelial-Mesenchymal Transition Computational Biology Protein Interaction Maps Biomarkers, Tumor Poly-ADP-Ribose Binding Proteins Carcinoma, Renal Cell Gene Expression Regulation, Neoplastic DNA Topoisomerases, Type II Humans Gene Expression Profiling Kinesins Prognosis
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