Computational prediction of phosphorylation sites with their cognate
protein kinases (PKs) is greatly helpful for further experimental
design. Although ~10 online predictors were developed, the PK
classification and control of false positive rate (FPR
) were not well addressed. Here we adopted a well-established rule to
classify PKs into a hierarchical structure with four levels. Also, we
developed a simple approach to estimate the theoretically maximal FPRs.
Then GPS 2.0
(Group-based Prediction System
, ver 2.0
) software was implemented in JAVA and could predict kinase-specific phosphorylation sites for 408
human PKs in hierarchy. As an application, we performed a
large-scale prediction of >13,000 mammalian phosphorylation sites
with high performances. In addition, we also provided a proteome-wide
prediction of Aurora-B specific substrates including protein-protein
interaction information. As the first stand-alone software for
computational phosphorylation, GPS 2.0 will be an excellent tool for
further experimental consideration and construction of phosphorylation
networks.
The GPS 2.0 is freely available at: http://gps.biocuckoo.org
<!-- null -->
GPS 2.0 User Interface
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