DeepKinZero: zero-shot learning for predicting kinase–phosphosite associations involving understudied kinases
Author(s) -
Iman Deznabi,
Busra Arabaci,
Mehmet Koyutürk,
Öznur Taştan
Publication year - 2020
Publication title -
bioinformatics
Language(s) - Uncategorized
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btaa013
Subject(s) - kinase , phosphorylation , biology , computational biology , map2k7 , protein phosphorylation , microbiology and biotechnology , computer science , cyclin dependent kinase 2 , protein kinase a
Protein phosphorylation is a key regulator of protein function in signal transduction pathways. Kinases are the enzymes that catalyze the phosphorylation of other proteins in a target-specific manner. The dysregulation of phosphorylation is associated with many diseases including cancer. Although the advances in phosphoproteomics enable the identification of phosphosites at the proteome level, most of the phosphoproteome is still in the dark: more than 95% of the reported human phosphosites have no known kinases. Determining which kinase is responsible for phosphorylating a site remains an experimental challenge. Existing computational methods require several examples of known targets of a kinase to make accurate kinase-specific predictions, yet for a large body of kinases, only a few or no target sites are reported.
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