Identification of Phosphorylation Sites Using SVMs
Protein phosphorylation, which is an important mechanism in posttranslational modification, affects essential cellular processes such as metabolism, cell signaling, differentiation, and membrane transportation. Proteins are phosphorylated by a variety of protein kinases. A predictor is constructed to predict the true and false phosphorylation sites based on support vector machines (SVM), and encoding method is used for amino sequences. Single variable models and multivariable models are applied to generate the input for the SVM. The main contribution here is that we have developed a kinase-specific phosphorylation site prediction tool with both high sensitivity and specificity.
Encoding method Support Vector Machines Phosphorylation Sites
Jinyan Huang Tonghua Li Kai Chen
School of Life Sciences and Technology, Tongji University, Shanghai, China, 200092 Department of Chemistry, Tongji University, Shanghai, China, 200092
国际会议
上海
英文
1200-1204
2008-05-16（万方平台首次上网日期，不代表论文的发表时间）