GPSD: a hybrid learning framework for the prediction of phosphatase-specific dephosphorylation sites.

ABSTRACT: Protein phosphorylation is dynamically and reversibly regulated by protein kinases and protein phosphatases, and plays an essential role in orchestrating a wide range of biological processes. Although a number of tools have been developed for predicting kinase-specific phosphorylation sites (p-sites), computational prediction of phosphatase-specific dephosphorylation sites remains to be a great challenge. In this study, we manually curated 4393 experimentally identified site-specific phosphatase-substrate relationships for 3463 dephosphorylation sites occurring on phosphoserine, phosphothreonine, and/or phosphotyrosine residues, from the literature and public databases. Then, we developed a hybrid learning framework, the group-based prediction system for the prediction of phosphatase-speci

SUBMITTER: Han C 

PROVIDER: S-EPMC11695897 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature