title: Rice_Phospho 1.0: a new rice-specific SVM predictor for protein phosphorylation sites.
abstract: Experimentally-determined or computationally-predicted protein phosphorylation sites for distinctive species are becoming increasingly common. In this paper, we compare the predictive performance of a novel classification algorithm with different encoding schemes to develop a rice-specific protein phosphorylation site predictor. Our results imply that the combination of Amino acid occurrence Frequency with Composition of K-Spaced Amino Acid Pairs (AF-CKSAAP) provides the best description of relevant sequence features that surround a phosphorylation site. A support vector machine (SVM) using AF-CKSAAP achieves the best performance in classifying rice protein phophorylation sites when compared to the other algorithms. We have used SVM with AF-CKSAAP to construct a rice-specific protein phosphorylation sites predictor, Rice_Phospho 1.0 (http://bioinformatics.fafu.edu.cn/rice_phospho1.0). We measure the Accuracy (ACC) and Matthews Correlation Coefficient (MCC) of Rice_Phospho 1.0 to be 82.0% and 0.64, significantly higher than those measures for other predictors such as Scansite, Musite, PlantPhos and PhosphoRice. Rice_Phospho 1.0 also successfully predicted the experimentally identified phosphorylation sites in LOC_Os03g51600.1, a protein sequence which did not appear in the training dataset. In summary, Rice_phospho 1.0 outputs reliable predictions of protein phosphorylation sites in rice, and will serve as a useful tool to the community.
authors.affiliation: College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
authors.forename: Shoukai
authors.initials: S
authors.lastname: Lin
authors.affiliation: College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
authors.forename: Qi
authors.initials: Q
authors.lastname: Song
authors.affiliation: College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
authors.forename: Huan
authors.initials: H
authors.lastname: Tao
authors.affiliation: College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
authors.forename: Wei
authors.initials: W
authors.lastname: Wang
authors.affiliation: College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
authors.forename: Weifeng
authors.initials: W
authors.lastname: Wan
authors.affiliation: College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
authors.forename: Jian
authors.initials: J
authors.lastname: Huang
authors.affiliation: College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
authors.forename: Chaoqun
authors.initials: C
authors.lastname: Xu
authors.affiliation: College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
authors.forename: Vivien
authors.initials: V
authors.lastname: Chebii
authors.affiliation: College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
authors.forename: Justine
authors.initials: J
authors.lastname: Kitony
authors.affiliation: College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
authors.forename: Shufu
authors.initials: S
authors.lastname: Que
authors.affiliation: Department of Mathematical Sciences, University of Essex, Wivenhoe Park, Colchester, CO4 3SQ, UK.
authors.forename: Andrew
authors.initials: A
authors.lastname: Harrison
authors.affiliation: College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
authors.forename: Huaqin
authors.initials: H
authors.lastname: He
mesh_terms: D000465:Algorithms; D019540:Area Under Curve; D020407:Internet; D012275:Oryza / Q000378:metabolism*; D010766:Phosphorylation; D010940:Plant Proteins / Q000737:chemistry / Q000378:metabolism*; D012372:ROC Curve; D060388:Support Vector Machine; D014584:User-Computer Interface
chemical_list: D010940:Plant Proteins