M3NetFlow: A novel multi-scale multi-hop graph AI model for integrative multi-omic data analysis.

ABSTRACT: Multi-omic data-driven studies, characterizing complex disease signaling system from multiple levels, are at the forefront of precision medicine and healthcare. The integration and interpretation of multi-omic data are essential for identifying molecular targets and deciphering core signaling pathways of complex diseases. However, it remains an open problem due the large number of biomarkers and complex interactions among them. In this study, we propose a novel Multi-scale Multi-hop Multi-omic graph model, M3NetFlow, to facilitate generic multi-omic data analysis to rank targets and infer core signaling flows/pathways. To evaluate M3NetFlow, we applied it in two independent multi-omic case studies: 1) uncovering mechanisms of synergistic drug combination response (defined as anchor-

SUBMITTER: Zhang H 

PROVIDER: S-EPMC11398409 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature