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
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