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 phosp

SUBMITTER: Lin S 

PROVIDER: S-EPMC4493637 | biostudies-literature | 2015 Jul

REPOSITORIES: biostudies-literature