KinasePhos: a web tool for identifying protein kinase-specific phosphorylation sites.
KinasePhos is a novel web server for computationally identifying catalytic kinase-specific phosphorylation sites. The known phosphorylation sites from public domain data sources are categorized by their annotated protein kinases. Based on the profile hidden Markov model, computational models are learned from the kinase-specific groups of the phosphorylation sites. After evaluating the learned models, the model with highest accuracy was selected from each kinase-specific group, for use in a web-based prediction tool for identifying protein phosphorylation sites. Therefore, this work developed a kinase-specific phosphorylation site prediction tool with both high sensitivity and specificity. The prediction tool is freely available at http://KinasePhos.mbc.nctu.edu.tw/.
Huang
Hsien-Da
HD
Department of Biological Science and Technology, Institute of Bioinformatics, National Chiao Tung University, Hsin-Chu 300, Taiwan.
Lee
Tzong-Yi
TY
Tzeng
Shih-Wei
SW
Horng
Jorng-Tzong
JT
D019295:Computational Biology / Q000379:methods*; D020407:Internet; D008390:Markov Chains; D010750:Phosphoproteins / Q000737:chemistry* / Q000378:metabolism; D010766:Phosphorylation; D011494:Protein Kinases / Q000378:metabolism*; D020539:Sequence Analysis, Protein / Q000379:methods*; D012984:Software
D010750:Phosphoproteins; D011494:Protein Kinases