Prediction of mucin-type O-glycosylation sites in mammalian proteins using the composition of k-spaced amino acid pairs

Background: As one of the most common protein post-translational modifications, glycosylation is involved in a variety of important biological processes. Computational identification of glycosylation sites in protein sequences becomes increasingly important in the post-genomic era. A new encoding scheme was employed to improve the prediction of mucin-type O-glycosylation sites in mammalian proteins. Results: A new protein bioinformatics tool, CKSAAP_OGlySite, was developed to predict mucintype O-glycosylation serine/threonine (S/T) sites in mammalian proteins. Using the composition of k-spaced amino acid pairs (CKSAAP) based encoding scheme, the proposed method was trained and tested in a new and stringent O-glycosylation dataset with the assistance of Support Vector Machine (SVM). When the ratio of O-glycosylation to non-glycosylation sites in training datasets was set as 1:1, 10-fold cross-validation tests showed that the proposed method yielded a high

• Type: Journal
• Year: 2008
• Where: BMCBI
• Authors: Yong-Zi Chen, Yu-Rong Tang, Zhi-Ya Sheng, Ziding Zhang
• Keywords: BMCBI 2008, Mammalian Proteins, O-glycosylation, Proteins