Multi-Omics Network Models of Disease Mechanisms

Complex diseases rarely arise from a single gene, protein, or pathway acting in isolation - they emerge from disruptions across interconnected molecular layers. Multi-omics approaches, integrating genomics, transcriptomics, proteomics, metabolomics, and epigenomics, offer an unprecedented opportunity to capture this complexity and reconstruct the network-level mechanisms driving disease onset and progression.This Research Topic invites contributions that develop and apply integrative bioinformatics methods to build multi-omics network models of disease. We welcome studies employing network inference, multi-layer network integration, machine learning, and systems biology approaches to identify disease-relevant modules, biomarkers, and regulatory mechanisms. Both methodological advances and applied studies across disease areas (cancer, neurodegenerative, metabolic, autoimmune, and infectious diseases, among others) are encouraged.Topics of interest include, but are not limited to:o Novel computational and statistical methods for multi-omics data integration and network constructiono Network-based identification of disease biomarkers, driver genes, or therapeutic targetso Machine learning and AI approaches for multi-omics network inferenceo Multi-layer/multiplex network models linking genetic, molecular, and phenotypic datao Applications of multi-omics networks to precision medicine and patient stratificationo Benchmarking and validation strategies for network-based disease modelso Tools, pipelines, and databases supporting multi-omics network analysisBy bringing together computational innovation and biological application, this Research Topic aims to advance our understanding of disease mechanisms and accelerate the translation of multi-omics data into actionable clinical insight Topic editors: Xudong Han, Bing Wang Source: https://www.frontiersin.org/research-topics/85553/multi-omics-network-models-of-disease-mechanisms