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KG2ML: integrating knowledge graphs and positive unlabeled learning for identifying disease-associated genes.

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第一作者： Praveen,Kumar

第一单位： Department of Internal Medicine, Translational Informatics Division, School of Medicine, University of New Mexico (UNM), Albuquerque, NM, United States.

作者： Praveen,Kumar ^[1] ; Vincent T,Metzger ^[1] ; Swastika T,Purushotham ^[1] ; Priyansh,Kedia ^[1] ; Cristian G,Bologa ^[1] ; Christophe G,Lambert ^[1] ; Jeremy J,Yang ^[1]

作者单位： Department of Internal Medicine, Translational Informatics Division, School of Medicine, University of New Mexico (UNM), Albuquerque, NM, United States. ^[1]

关键词 DDKG GWAS biomedical knowledge graphs data distillery knowledge graph disease-associated genes genome-wide association studies linkage analysis network-based methods

DOI 10.3389/fbinf.2025.1727953

PMID 41584517

发布时间 2026-02-04

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KG2ML: integrating knowledge graphs and positive unlabeled learning for identifying disease-associated genes.

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KG2ML: integrating knowledge graphs and positive unlabeled learning for identifying disease-associated genes.

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