GPS 2.1: enhanced prediction of kinase-specific phosphorylation sites with an algorithm of motif length selection.
As the most important post-translational modification of proteins, phosphorylation plays essential roles in all aspects of biological processes. Besides experimental approaches, computational prediction of phosphorylated proteins with their kinase-specific phosphorylation sites has also emerged as a popular strategy, for its low-cost, fast-speed and convenience. In this work, we developed a kinase-specific phosphorylation sites predictor of GPS 2.1 (Group-based Prediction System), with a novel but simple approach of motif length selection (MLS). By this approach, the robustness of the prediction system was greatly improved. All algorithms in GPS old versions were also reserved and integrated in GPS 2.1. The online service and local packages of GPS 2.1 were implemented in JAVA 1.5 (J2SE 5.0) and freely available for academic researches at: http://gps.biocuckoo.org.
Hubei Bioinformatics and Molecular Imaging Key Laboratory, Department of Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China. xueyu@mail.hust.edu.cn
Yu
Y
Xue
Zexian
Z
Liu
Jun
J
Cao
Qian
Q
Ma
Xinjiao
X
Gao
Qingqi
Q
Wang
Changjiang
C
Jin
Yanhong
Y
Zhou
Longping
L
Wen
Jian
J
Ren
D000465:Algorithms; D020816:Amino Acid Motifs; D001665:Binding Sites; D019295:Computational Biology / Q000379:methods*; D006801:Humans; D010455:Peptides / Q000737:chemistry / Q000378:metabolism; D011494:Protein Kinases / Q000378:metabolism*; D015203:Reproducibility of Results; D012984:Software
D010455:Peptides; D011494:Protein Kinases