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Nucleic Acids Research Advance Access originally published online on May 21, 2007
Nucleic Acids Research 2007 35(Web Server issue):W588-W594; doi:10.1093/nar/gkm322
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Nucleic Acids Research, 2007, Vol. 35, No. suppl_2 W588-W594
© 2007 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Articles

KinasePhos 2.0: a web server for identifying protein kinase-specific phosphorylation sites based on sequences and coupling patterns

Yung-Hao Wong1, Tzong-Yi Lee1, Han-Kuen Liang2,4, Chia-Mao Huang3, Ting-Yuan Wang1, Yi-Huan Yang1, Chia-Huei Chu1, Hsien-Da Huang1,2,3,*, Ming-Tat Ko4 and Jenn-Kang Hwang1,2,3

1Institute of Bioinformatics, 2Department of Biological Science and Technology, 3Core Facility for Structural Bioinformatics, National Chiao Tung University, Hsin-chu 300, Taiwan and 4Institute of Information Science, Academia Sinica, 128sec. 2, Academia Rd, Taipei, Taiwan

*To whom correspondence should be addressed. Tel: +886 3 5712121 Ext. 56952; Fax: +886 3 5729288; Email: bryan{at}mail.nctu.edu.tw

Received January 31, 2007. Revised April 10, 2007. Accepted April 17, 2007.

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 CXdZ 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/.

The authors wish it to be known that, in their opinion, the first two authors should be regarded as joint First Authors


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