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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| Published in: | PeerJ (San Francisco, CA) Vol. 11; p. e15815 |
|---|---|
| Main Authors: | , , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
United States
PeerJ. Ltd
18.10.2023
PeerJ Inc |
| Subjects: | |
| ISSN: | 2167-8359, 2167-8359 |
| Online Access: | Get full text |
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