mosGraphFlow: a novel integrative graph AI model mining disease targets from multi-omic data.


Journal

bioRxiv : the preprint server for biology
ISSN: 2692-8205
Titre abrégé: bioRxiv
Pays: United States
ID NLM: 101680187

Informations de publication

Date de publication:
03 Sep 2024
Historique:
medline: 17 9 2024
pubmed: 17 9 2024
entrez: 16 9 2024
Statut: epublish

Résumé

Multi-omic data can better characterize complex cellular signaling pathways from multiple views compared to individual omic data. However, integrative multi-omic data analysis to rank key disease biomarkers and infer core signaling pathways remains an open problem. In this study, our novel contributions are that we developed a novel graph AI model,

Identifiants

pubmed: 39282361
doi: 10.1101/2024.08.01.606219
pmc: PMC11398418
pii:
doi:

Types de publication

Journal Article Preprint

Langues

eng

Auteurs

Classifications MeSH