SiteSeek: Post-translational modification analysis using adaptive locality-effective kernel methods and new profiles

Background: Post-translational modifications have a substantial influence on the structure and functions of protein. Post-translational phosphorylation is one of the most common modification that occur in intracellular proteins. Accurate prediction of protein phosphorylation sites is of great importance for the understanding of diverse cellular signalling processes in both the human body and in animals. In this study, we propose a new machine learning based protein phosphorylation site predictor, SiteSeek. SiteSeek is trained using a novel compact evolutionary and hydrophobicity profile to detect possible protein phosphorylation sites for a target sequence. The newly proposed method proves to be more accurate and exhibits a much stable predictive performance than currently existing phosphorylation site predictors. Results: The performance of the proposed model was compared to nine existing different machine learning models and four widely known phosphorylation site predictors with the...

• Type: Journal
• Year: 2008
• Where: BMCBI
• Authors: Paul D. Yoo, Yung Shwen Ho, Bing Bing Zhou, Albert Y. Zomaya
• Keywords: BMCBI 2008, Phosphorylation Site Predictors, Phosphorylation Sites, Protein Phosphorylation Sites