標題: KinasePhos 2.0: a web server for identifying protein kinase-specific phosphorylation sites based on sequences and coupling patterns
作者: Wong, Yung-Hao
Lee, Tzong-Yi
Liang, Han-Kuen
Huang, Chia-Mao
Wang, Ting-Yuan
Yang, Yi-Huan
Chu, Chia-Huei
Huang, Hsien-Da
Ko, Ming-Tat
Hwang, Jenn-Kang
生物科技學系
生物資訊及系統生物研究所
Department of Biological Science and Technology
Institude of Bioinformatics and Systems Biology
公開日期: 1-七月-2007
摘要: Due to the importance of protein phosphorylation in cellular control, many researches are undertaken to predict the kinase-specific phosphorylation sites. Referred to our previous work, KinasePhos 1.0, incorporated profile hidden Markov model (HMM) with flanking residues of the kinase-specific phosphorylation sites. Herein, a new web server, KinasePhos 2.0, incorporates support vector machines (SVM) with the protein sequence profile and protein coupling pattern, which is a novel feature used for identifying phosphorylation sites. The coupling pattern [XdZ] denotes the amino acid coupling-pattern of amino acid types X and Z that are separated by d amino acids. The differences or quotients of coupling strength C-XdZ between the positive set of phosphorylation sites and the background set of whole protein sequences from Swiss-Prot are computed to determine the number of coupling patterns for training SVM models. After the evaluation based on k-fold cross-validation and Jackknife cross-validation, the average predictive accuracy of phosphorylated serine, threonine, tyrosine and histidine are 90, 93, 88 and 93%, respectively. KinasePhos 2.0 performs better than other tools previously developed. The proposed web server is freely available at http://KinasePhos2.mbc.nctu.edu.tw/.
URI: http://dx.doi.org/10.1093/nar/gkm322
http://hdl.handle.net/11536/10620
ISSN: 0305-1048
DOI: 10.1093/nar/gkm322
期刊: NUCLEIC ACIDS RESEARCH
Volume: 35
Issue: 
起始頁: W588
結束頁: W594
顯示於類別:期刊論文


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