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 |