AIMC Topic: Computational Biology
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Interpretable bioinformatics approaches for pheochromocytoma bioactivity and protein interaction analysis.
Computers in biology and medicine
Aug 2, 2025
Pheochromocytoma (PCC) is a rare neuroendocrine tumor driven by complex molecular mechanisms, notably involving the oncogenic c-Myc/Max and c-Myc/c-Max protein complexes. Despite their pivotal role in tumor progression, the molecular interactions and...
Bind: large-scale biological interaction network discovery through knowledge graph-driven machine learning.
Journal of translational medicine
Jul 31, 2025
BACKGROUND: Biological systems derive from complex interactions between entities ranging from biomolecules to macroscopic structures, forming intricate networks essential for understanding disease mechanisms and developing therapeutic interventions. ...
Uncovering active ingredients and mechanisms of Pholiota adiposa in the treatment of Alzheimer's disease based on network pharmacology and bioinformatics.
Scientific reports
Jul 31, 2025
Pholiota adiposa is recognized for its health benefits, particularly in Alzheimer's disease (AD), but its molecular mechanism remains elusive. Our study employs network pharmacology and machine learning to uncover its therapeutic potential. We constr...
Identification of DNA damage response and crotonylation-related biomarkers for lung adenocarcinoma via machine learning and WGCNA.
Clinical and experimental medicine
Jul 30, 2025
DNA damage response (DDR) and crotonylation occur frequently in lung adenocarcinoma (LUAD), but their relationship is yet to be elucidated. RNA sequencing data from LUAD patients in GSE27262 and GSE140797 datasets were obtained. DDR-crotonylation-rel...
Drug-target interaction prediction based on graph convolutional autoencoder with dynamic weighting residual GCN.
BMC bioinformatics
Jul 29, 2025
BACKGROUND: The exploration of drug-target interactions (DTIs) is a critical step in drug discovery and drug repurposing. Recently, network-based methods have emerged as a prominent research area for predicting DTIs. These methods excel by extracting...
Interpretable graph Kolmogorov-Arnold networks for multi-cancer classification and biomarker identification using multi-omics data.
Scientific reports
Jul 29, 2025
The integration of heterogeneous multi-omics datasets at a systems level remains a central challenge for developing analytical and computational models in precision cancer diagnostics. This paper introduces Multi-Omics Graph Kolmogorov-Arnold Network...
Exploring the comorbidity mechanisms of ITGB2 in rheumatoid arthritis and membranous nephropathy through integrated bioinformatics analysis.
Renal failure
Jul 23, 2025
BACKGROUND: Patients with rheumatoid arthritis (RA) are more likely to comorbid renal diseases, with membranous nephropathy (MN) being the most common. This study aimed to explore the common pathogenesis between RA and MN using integrated bioinformat...
A computational pipeline for predicting distal hotspots in an artificial enzyme.
International journal of biological macromolecules
Jul 23, 2025
Targeting distal mutations holds promising implications for enzyme engineering. Here, we present an open-source computational workflow designed to explore the functional impact of distal sites, demonstrated on an artificial enzyme built on the widely...
m5U-HybridNet: Integrating an RNA Foundation Model with CNN Features for Accurate Prediction of 5-Methyluridine Modification Sites.
Journal of chemical information and modeling
Jul 22, 2025
The 5-methyluridine (m5U) modification in RNA is vital for numerous biological processes, making its precise identification a key focus in computational biology. However, traditional wet-lab detection methods are cumbersome and time-consuming, wherea...
BPFun: a deep learning framework for bioactive peptide function prediction using multi-label strategy by transformer-driven and sequence rich intrinsic information.
BMC bioinformatics
Jul 21, 2025
Bioactive peptides are beneficial or have physiological effects on the life activities of biological organisms. The functions of bioactive peptides are diverse, usually with one or more, so accurately detecting the multiple functions of multi-functio...
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