AIMC Topic: GTPase-Activating Proteins

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Machine learning in Alzheimer's disease genetics.

Nature communications Jul 22, 2025
Traditional statistical approaches have advanced our understanding of the genetics of complex diseases, yet are limited to linear additive models. Here we applied machine learning (ML) to genome-wide data from 41,686 individuals in the largest Europe...
Humans Neural Networks, Computer Genetic Predisposition to Disease Polymorphism, Single Nucleotide Alzheimer Disease GTPase-Activating Proteins Machine Learning Algorithms Genome-Wide Association Study
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Machine learning models reveal ARHGAP11A's impact on lymph node metastasis and stemness in NSCLC.

BioFactors (Oxford, England) Oct 31, 2024
Most patients with non-small cell lung cancer (NSCLC) are diagnosed at an advanced stage of the disease, which complicates treatment due to a heightened risk of metastasis. Consequently, the timely identification of biomarkers associated with lymph n...
Machine Learning Prognosis Female Humans Cell Line, Tumor Lung Neoplasms Gene Expression Regulation, Neoplastic Cell Proliferation Biomarkers, Tumor Male Middle Aged GTPase-Activating Proteins Neoplastic Stem Cells Carcinoma, Non-Small-Cell Lung Lymphatic Metastasis
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Integrating bioinformatics and machine learning methods to analyze diagnostic biomarkers for HBV-induced hepatocellular carcinoma.

Diagnostic pathology Aug 2, 2024
Hepatocellular carcinoma (HCC) is a malignant tumor. It is estimated that approximately 50-80% of HCC cases worldwide are caused by hepatitis b virus (HBV) infection, and other pathogenic factors have been shown to promote the development of HCC when...
Databases, Genetic GTPase-Activating Proteins Liver Neoplasms Carcinoma, Hepatocellular Hepatitis B virus Hepatitis B Computational Biology Machine Learning Gene Expression Regulation, Neoplastic Biomarkers, Tumor Gene Expression Profiling Humans
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RACGAP1 is a pivotal gene in lung adenocarcinoma-associated membranous nephropathy: Based on comprehensive bioinformatics analysis and machine learning.

International immunopharmacology Jul 27, 2024
BACKGROUND: This study performs a detailed bioinformatics and machine learning analysis to investigate the genetic foundations of membranous nephropathy (MN) in lung adenocarcinoma (LUAD).
Adenocarcinoma of Lung GTPase-Activating Proteins Gene Expression Profiling Lung Neoplasms Computational Biology Glomerulonephritis, Membranous Female Gene Expression Regulation, Neoplastic Humans Collagen Type III Databases, Genetic Male Machine Learning Middle Aged Prognosis
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Identification of DEP domain-containing proteins by a machine learning method and experimental analysis of their expression in human HCC tissues.

Scientific reports Dec 21, 2016
The Dishevelled/EGL-10/Pleckstrin (DEP) domain-containing (DEPDC) proteins have seven members. However, whether this superfamily can be distinguished from other proteins based only on the amino acid sequences, remains unknown. Here, we describe a com...
Signal Transduction Cluster Analysis Protein Domains Amino Acid Motifs GTPase-Activating Proteins Algorithms Dishevelled Proteins Computational Biology Phylogeny RNA, Messenger Gene Expression Profiling Humans Real-Time Polymerase Chain Reaction Gene Expression Regulation, Neoplastic Machine Learning Liver Neoplasms Carcinoma, Hepatocellular
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Machine Learning-based Classification of Diffuse Large B-cell Lymphoma Patients by Their Protein Expression Profiles.

Molecular & cellular proteomics : MCP Aug 26, 2015
Characterization of tumors at the molecular level has improved our knowledge of cancer causation and progression. Proteomic analysis of their signaling pathways promises to enhance our understanding of cancer aberrations at the functional level, but ...
Neprilysin Phosphoprotein Phosphatases Tissue Embedding Proteomics Lymphoma, Large B-Cell, Diffuse Tissue Fixation Neoplasm Proteins Apoptosis Regulatory Proteins Humans Proteome Cell Line, Tumor Signal Transduction Isotope Labeling Gene Expression Regulation, Neoplastic Machine Learning Principal Component Analysis GTPase-Activating Proteins Biomarkers, Tumor Formaldehyde
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The interaction of UBR4, LRP1, and OPHN1 in refractory epilepsy: Drosophila model to investigate the oligogenic effect on epilepsy.

Neurobiology of disease Aug 1, 2025
Refractory epilepsy is an intractable neurological disorder that can be associated with oligogenic/polygenic etiologies. Through trio-based whole-exome sequencing analysis, we identified a clinical case of refractory epilepsy with three candidate gen...
Low Density Lipoprotein Receptor-Related Protein-1 Animals Drosophila Male Drug Resistant Epilepsy Humans Disease Models, Animal GTPase-Activating Proteins Animals, Genetically Modified Female Drosophila Proteins Ubiquitin-Protein Ligases
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