AIMC Topic: Gene Ontology

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Genome-scale prediction of gene ontology from mass fingerprints reveals new metabolic gene functions.

Life science alliance
Mass-based fingerprinting can characterize microorganisms; however, expansion of these methods to predict specific gene functions is lacking. Therefore, mass fingerprinting was developed to functionally profile a yeast knockout library. Matrix-assist...

ProteinWeaver: A webtool to visualize ontology-annotated protein networks.

PloS one
Molecular interaction networks are a vital tool for studying biological systems. While many tools exist that visualize a protein or a pathway within a network, no tool provides the ability for a researcher to consider a protein's position in a networ...

Identification of core genes in the extracellular matrix and the regulatory mechanisms of the immune microenvironment in idiopathic pulmonary fibrosis using WGCNA and machine learning methods.

PloS one
OBJECTIVE: This research aims to detect genes associated with the extracellular matrix (ECM) in idiopathic pulmonary fibrosis (IPF) using bioinformatics techniques and investigate their relationships with immune infiltration, with the goal of identif...

Immunophenotyping identifies key immune biomarkers for coronary artery disease through machine learning.

PloS one
INTRODUCTION: The differences among immune subtypes in coronary artery disease (CAD), their interrelationships, and the associated immune biomarkers remain incompletely understood.

Aging associated immunosenescence in rheumatoid arthritis identified by machine learning and single cell profiling.

Scientific reports
Rheumatoid arthritis (RA) is increasingly prevalent among older adults, who often experience more severe symptoms and face significant treatment challenges. This study aims to identify specific genes associated with aging in RA and to analyze their i...

Sparse autoencoders uncover biologically interpretable features in protein language model representations.

Proceedings of the National Academy of Sciences of the United States of America
Foundation models in biology-particularly protein language models (PLMs)-have enabled ground-breaking predictions in protein structure, function, and beyond. However, the "black-box" nature of these representations limits transparency and explainabil...

Construction of a feature gene and machine prediction model for inflammatory bowel disease based on multichip joint analysis.

Journal of translational medicine
BACKGROUND: Inflammatory bowel disease (IBD) is a chronic nonspecific inflammatory disorder triggered by immune responses and genetic factors. Currently, there is no cure for IBD, and its etiology remains unclear. As a result, early detection and dia...

Network-based approach identifies key genes associated with tumor heterogeneity in HPV positive and negative head and neck cancer patients.

Scientific reports
Head and Neck Squamous Cell Carcinoma (HNSCC) is the seventh most prevalent cancer worldwide and is classified as human papillomavirus (HPV) positive or negative. Substantial heterogeneity has been observed in the two groups, posing a significant cli...

A deep ensemble framework for human essential gene prediction by integrating multi-omics data.

Scientific reports
Essential genes are necessary for the survival or reproduction of a living organism. The prediction and analysis of gene essentiality can advance our understanding of basic life and human diseases, and further boost the development of new drugs. We p...

Prediction of hub genes in pulpal inflammation and regeneration using autoencoders and a generative AI approach.

Scientific reports
Pulpal inflammation and regeneration are crucial for enhancing endodontic treatment outcomes. Transcriptomic studies highlight the involvement of proinflammatory cytokines, NF-κB signaling, and stem cell activity. This study employs a generative AI a...