AIMC Topic: Computational Biology
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Identification of biomarkers in Alzheimer's disease and COVID-19 by bioinformatics combining single-cell data analysis and machine learning algorithms.
PloS one
Feb 18, 2025
BACKGROUND: Since its emergence in 2019, COVID-19 has become a global epidemic. Several studies have suggested a link between Alzheimer's disease (AD) and COVID-19. However, there is little research into the mechanisms underlying these phenomena. The...
MVGNCDA: Identifying Potential circRNA-Disease Associations Based on Multi-view Graph Convolutional Networks and Network Embeddings.
Interdisciplinary sciences, computational life sciences
Feb 17, 2025
Increasing evidences have indicated that circular RNAs play a crucial role in the onset and progression of various diseases. However, exploring potential disease-associated circRNAs using conventional experimental techniques remains both time-intensi...
Identification of benzo(a)pyrene-related toxicological targets and their role in chronic obstructive pulmonary disease pathogenesis: a comprehensive bioinformatics and machine learning approach.
BMC pharmacology & toxicology
Feb 17, 2025
BACKGROUND: Chronic obstructive pulmonary disease (COPD) pathogenesis is influenced by environmental factors, including Benzo(a)pyrene (BaP) exposure. This study aims to identify BaP-related toxicological targets and elucidate their roles in COPD dev...
Key RNA-binding proteins in renal fibrosis: a comprehensive bioinformatics and machine learning framework for diagnostic and therapeutic insights.
Renal failure
Feb 16, 2025
BACKGROUND: Renal fibrosis is a critical factor in chronic kidney disease progression, with limited diagnostic and therapeutic options. Emerging evidence suggests RNA-binding proteins (RBPs) are pivotal in regulating cellular mechanisms underlying fi...
RNA-protein interaction prediction using network-guided deep learning.
Communications biology
Feb 16, 2025
Accurate computational determination of RNA-protein interactions remains challenging, particularly when encountering unknown RNAs and proteins. The limited number of RNAs and their flexibility constrained the effectiveness of the deep-learning models...
Identifying RNA-small Molecule Binding Sites Using Geometric Deep Learning with Language Models.
Journal of molecular biology
Feb 15, 2025
RNAs are emerging as promising therapeutic targets, yet identifying small molecules that bind to them remains a significant challenge in drug discovery. This underscores the crucial role of computational modeling in predicting RNA-small molecule bind...
Identification of biomarkers associated with phagocytosis regulatory factors in coronary artery disease using machine learning and network analysis.
Mammalian genome : official journal of the International Mammalian Genome Society
Feb 14, 2025
BACKGROUND: Coronary artery disease (CAD) is the leading cause of death worldwide, and aberrant phagocytosis may be involved in its development. Understanding this aspect may provide new avenues for prompt CAD diagnosis.
Computational Biology
Transcription Factors
Databases, Genetic
Protein Interaction Maps
Gene Regulatory Networks
Polymorphism, Single Nucleotide
Phagocytosis
Machine Learning
Humans
Toll-Like Receptor 2
MicroRNAs
Receptors, IgG
Biomarkers
Syk Kinase
Interleukin-1beta
Gene Expression Profiling
Coronary Artery Disease
Artificial Intuition and accelerating the process of antimicrobial drug discovery.
Computers in biology and medicine
Feb 14, 2025
New drug development is a very challenging, expensive, and usually time-consuming process. This issue is very important with regard to antimicrobials, which are affected by the global issue of the development and spread of resistance. This framework ...
Interpretable AI for inference of causal molecular relationships from omics data.
Science advances
Feb 14, 2025
The discovery of molecular relationships from high-dimensional data is a major open problem in bioinformatics. Machine learning and feature attribution models have shown great promise in this context but lack causal interpretation. Here, we show that...
Probing the eukaryotic microbes of ruminants with a deep-learning classifier and comprehensive protein databases.
Genome research
Feb 14, 2025
Metagenomics, particularly genome-resolved metagenomics, have significantly deepened our understanding of microbes, illuminating their taxonomic and functional diversity and roles in ecology, physiology, and evolution. However, eukaryotic populations...
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