Predicting protein and pathway associations for understudied dark kinases using pattern-constrained knowledge graph embedding

The 534 protein kinases encoded in the human genome constitute a large druggable class of proteins that include both well-studied and understudied “dark” members. Accurate prediction of dark kinase functions is a major bioinformatics challenge. Here, we employ a graph mining approach that uses the e...

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Veröffentlicht in:PeerJ (San Francisco, CA) Jg. 11; S. e15815
Hauptverfasser: Salcedo, Mariah V., Gravel, Nathan, Keshavarzi, Abbas, Huang, Liang-Chin, Kochut, Krzysztof J., Kannan, Natarajan
Format: Journal Article
Sprache:Englisch
Veröffentlicht: United States PeerJ. Ltd 18.10.2023
PeerJ Inc
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ISSN:2167-8359, 2167-8359
Online-Zugang:Volltext
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