Multi-source biological knowledge-guided hypergraph spatiotemporal subnetwork embedding for protein complex identification.

ABSTRACT: Identifying biologically significant protein complexes from protein-protein interaction (PPI) networks and understanding their roles are essential for elucidating protein functions, life processes, and disease mechanisms. Current methods typically rely on static PPI networks and model PPI data as pairwise relationships, which presents several limitations. Firstly, static PPI networks do not adequately represent the scopes and temporal dynamics of protein interactions. Secondly, a large amount of available biological resources have not been fully integrated. Moreover, PPIs in biological systems are not merely one-to-one relationships but involve higher order non-pairwise interactions. To alleviate these issues, we propose HGST, a multi-source biological knowledge-guided hypergraph spatiotem

SUBMITTER: Wang S 

PROVIDER: S-EPMC11735048 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature