Bioinformatics and Genomic Networks

A Novel ILP Framework to Identify Compensatory Pathways in Genetic Interaction Networks with GIDEON

The paper introduces GIDEON, an ILP framework to identify compensatory pathways in yeast genetic interaction networks, finding new BPM gene sets with potential antifungal drug target insights.

DIVAS: an R package for identifying shared and individual variations of multiomics data

DIVAS identifies shared and individual variations in multiomics data, revealing partially shared patterns missed by existing methods.

hypeR-GEM: connecting metabolite signatures to enzyme-coding genes via genome-scale metabolic models

hypeR-GEM connects metabolite signatures to enzyme-coding genes using genome-scale metabolic models, showing concordance with proteomic and transcriptomic data in real-world applications.

A module-based approach for post-omics, post-GWAS network-based gene classification

The paper introduces ModGenePlexus, a network-based gene classification method that improves disease gene discovery by decomposing gene lists into modules and combining module-specific classifiers.

LLM-powered Functional Gene Set Summarization with genesetGPT

genesetGPT is an LLM-based framework that improves gene set annotation by using curated biological context and iterative prompt design to summarize heterogeneous gene sets.

Hypergraph geometry localizes mutation-associated dependency vulnerabilities in cancer.

The paper identifies mutation-associated therapeutic vulnerabilities in cancer using hypergraph geometry and CRISPR screens, finding specific dependencies with drug sensitivity.

LNGCN: a distance-aware continuous-time graph framework for PPI prioritization in experimental screening

LNGCN improves PPI prioritization by using a distance-aware continuous-time graph framework, achieving high precision on imbalanced datasets and preserving residue-level representation diversity.

PlantMetWiki: a FAIR knowledge graph for plant metabolic pathway cross-species representation and integration

PlantMetWiki integrates plant metabolic pathway data across species to enable cross-species analysis and hypothesis generation.

Complex Assembly and Activity States as Multifaceted Protein Attributes Explaining Phenotypic Variability

The paper introduces a multi-omics framework to analyze protein activity in context-specific networks, demonstrating its utility in linking molecular profiles to phenotypic outcomes using HeLa and Kyoto cell lines.

BioPhasor: Decoding Cellular State Tensors from Multi-Omics Phasor Dynamics for Quantum Ready Systems Biology

The paper introduces BioPhasor, a framework that models cellular states using phasor dynamics and multi-omics data, showing improved performance in cell-cycle and circadian analysis.

Graph Lens Lite: A browser-based tool for interactive visualization and exploration of biological networks

Graph Lens Lite is a browser-based tool for visualizing and exploring biological networks, offering interactive features for analysis and hypothesis generation in disease and drug research.

CSOA: A Novel Single-Cell Gene Set Enrichment Analysis Method with Comprehensive Benchmarking

CSOA improves gene set enrichment analysis in single-cell data by accurately distinguishing enriched cells from background, outperforming existing methods in multiple benchmarks.

GeneAutomate: A Browser-Based, Integer-Indexed Platform for Dual-Gene-List Functional Annotation and Interactive Network Visualization

GeneAutomate provides a browser-based tool for comparing two gene lists with ORA, GSEA, and interactive visualizations, avoiding installation and server dependencies.

Leveraging multiplicity in biologically informed neural networks to uncover disease heterogeneity

The paper presents a fast BINN implementation trained on UK Biobank data to predict disease, revealing limitations in interpretability and showing that model multiplicity can reveal disease heterogeneity.

A conundrum of pleiotropy: GWAS-derived pleiotropy is weakly negatively associated with co-expression network centrality in Arabidopsis thaliana

Textural features for pathway-level representation of omics data in biological networks

This paper adapts Haralick texture analysis to biological networks to generate pathway-level features from gene-level omics data, showing comparable performance to existing methods and potential for drug response prediction.

Differential multi-omics analysis of pulmonary arterial hypertension microvascular endothelial cells for differential drug response

The paper uses a multi-omics framework to analyze PAH endothelial cells and identifies kinase-related alterations and potential drug targets.

Predicting the protein interaction landscape of a mycobacterial pathogen

The paper uses AI-based protein-protein interaction predictions to characterize protein function in mycobacterial pathogens, identifying key interactions and functions for previously uncharacterized proteins.

MSstatsBioNet: Integrating Statistical Analyses with Prior Knowledge Biomolecular Networks for Quantitative Proteomics and Phosphoproteomics

MSstatsBioNet integrates differential proteomics results with biomolecular networks to enable mechanistic interpretation of biological changes.

Lemonite: identification of regulatory metabolites through data-driven, interpretable integration of transcriptomics and metabolomics data

Lemonite integrates transcriptomics and metabolomics data to identify regulatory metabolites acting on gene modules in glioblastoma and inflammatory bowel disease.

Sex-Dimorphic Aging of Cardiovascular Disease Genes: A Network-Based Multi-Omics Analysis

This study identifies sex-dimorphic aging patterns in cardiovascular disease genes using multi-omics data and prioritizes actionable biomarkers with convergent evidence.

The landscape of plasma proteomic links to human organ imaging

The paper maps phenotypic and genetic links between plasma proteins and organ imaging traits using UK Biobank data, identifying associations and causal links across multiple organs.

A deep-learning-informed prior and Bayesian model for differential AP-MS interactome analysis

BayesInteractomics improves AP-MS interactome analysis by combining deep learning and Bayesian statistics to better distinguish true interactions from background noise.

A five-dimensional functional state space for fingerprinting disease transcriptomes

The paper introduces a five-dimensional functional state space to represent disease transcriptomes as interpretable fingerprints, improving human-AI interpretation and cross-condition profiling.

ORBIT: Annotation-Aware Empirical Enrichment and Semantic Reranking for Interpretable Functional-Class Recovery

ORBIT improves gene-set interpretation by combining empirical enrichment, semantic reranking, and redundancy reduction to provide interpretable functional summaries.

HetNetEX: Exact Asymptotic Inference in Heterogeneous Biomedical Knowledge Graphs

HetNetEX provides exact asymptotic inference for connectivity in heterogeneous biomedical knowledge graphs, outperforming XSwap in speed and accuracy.

OMIDIENT: Multiomics Integration for Cancer by Dirichlet Auto-Encoder Networks

OMIDIENT is a multi-omics integration method that uses Dirichlet auto-encoders to improve clustering, classification, and data reconstruction across cancer types.

Biological Network Organization, Not Generic Graph Topology, Drives Graph-Based Gene Essentiality Prediction

This study evaluates whether graph-based gene essentiality prediction relies on biological network structure or generic graph topology, finding that biological connectivity is critical for performance.

Zero-Shot Metabolite Prediction from Gene Expression via Physics-Informed Graph Neural Networks

GAZE predicts metabolite concentrations from gene expression using a physics-informed graph neural network, achieving better performance than existing methods in zero-shot scenarios.

PlantMDCS: A code-free, modular toolkit for rapid deployment of plant multi-omics databases

PlantMDCS provides a code-free, modular platform for deploying plant multi-omics databases, enabling efficient data management and analysis without programming expertise.