AIMC Topic: Computational Biology

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Key RNA-binding proteins in renal fibrosis: a comprehensive bioinformatics and machine learning framework for diagnostic and therapeutic insights.

Renal failure
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...

Identification and validation of susceptibility modules and hub genes in polyarticular juvenile idiopathic arthritis using WGCNA and machine learning.

Autoimmunity
BACKGROUND: Juvenile idiopathic arthritis (JIA), superseding juvenile rheumatoid arthritis (JRA), is a chronic autoimmune disease affecting children and characterized by various types of childhood arthritis. JIA manifests clinically with joint inflam...

Results of the Protein Engineering Tournament: An Open Science Benchmark for Protein Modeling and Design.

Proteins
The grand challenge of protein engineering is the development of computational models to characterize and generate protein sequences for arbitrary functions. Progress is limited by lack of (1) benchmarking opportunities, (2) large protein function da...

An effective statistical moment-based feature extraction technique to identify the phosphoglycerylation sites from protein sequences.

Journal of molecular graphics & modelling
A kind of covalent modification known as post-translational modification (PTM) happens following the biosynthesis process, which is important in cell biology research. A reversible PTM called Lysine phosphoglycerylation alters glycolytic enzyme activ...

Identification and validation of feature genes in hepatocellular carcinoma based on bioinformatics and machine learning: An observational study.

Medicine
The incidence of hepatocellular carcinoma (HCC) has risen significantly in recent years, while current diagnostic and therapeutic approaches remain suboptimal. This study aimed to identify novel biomarkers and therapeutic targets to improve early det...

Integrated bioinformatics analysis and machine learning identifies FZD4, SRPX2, and COL8A1 as angiogenesis hub genes in endometriosis.

Medicine
This study aims to identify angiogenesis-associated genes (AAGs) in endometriosis (EM) by integrating bioinformatics analysis with machine learning, and to investigate their underlying mechanisms. Differentially expressed genes (DEGs) were screened f...

ZNF143 as a diagnostic biomarker: Insights from gene expression and immune cell infiltration in COPD and asthma.

Medicine
Chronic obstructive pulmonary disease (COPD) and asthma are common and serious respiratory diseases worldwide. Their clinical overlap and lack of specificity in current biomarkers pose a great diagnostic challenge for early diagnosis. To address this...

Exploring the unique characteristics of genes with dual autosomal dominant and recessive inheritance: mechanisms, phenotypes and candidate identification.

Journal of medical genetics
BACKGROUND: Autosomal dominant (AD) inheritance often arises through haploinsufficiency, dominant-negative or gain of function (GoF) effects, while autosomal recessive (AR) inheritance generally results from partial or complete loss of function (LoF)...

Computational prediction of mutagenicity through comprehensive cell painting analysis.

Mutagenesis
The mutagenicity of chemical compounds is a key consideration in toxicology, drug development, and environmental safety. Traditional methods such as the Ames test, while reliable, are time-intensive and costly. With advances in imaging and machine le...

From Harmony to Discord: Multicellular Coordination in Tissues and Its Rewiring in Cancer.

Cancer research
Tissue function emerges from coordinated interactions among diverse cell types, but how these interactions are structured and rewired in disease remains unclear. In a recent study, Shi and colleagues introduce CoVarNet, a computational framework that...