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Indexed by:期刊论文

Date of Publication:2016-05-21

Journal:JOURNAL OF THEORETICAL BIOLOGY

Included Journals:PubMed、SCIE、Scopus

Volume:397

Issue:397

Page Number:145-150

ISSN No.:0022-5193

Key Words:Post-translational modification; Phosphoglycerylation; k-spaced amino acid pairs; Fuzzy support vector machine

Abstract:As a new type of post-translational modification, lysine phosphoglycerylation plays a key role in regulating glycolytic process and metabolism in cells. Due to the traditional experimental methods are time-consuming and labor-intensive, it is important to develop computational methods to identify the potential phosphoglycerylation sites. However, the prediction performance of the existing phosphoglycerylation site predictor is not satisfactory. In this study, a novel predictor named CKSAAP_PhoglySite is developed to predict phosphoglycerylation sites by using composition of k-spaced amino acid pairs and fuzzy support vector machine. On the one hand, after many aspects of assessments, we find the composition of k-spaced amino acid pairs is more suitable for representing the protein sequence around the phosphoglycerylation sites than other encoding schemes. On the other hand, the proposed fuzzy support vector machine algorithm can effectively handle the imbalanced and noisy problem in phosphoglycerylation sites training dataset. Experimental results indicate that CKSAAP_PhoglySite outperforms the existing phosphoglycerylation site predictor Phogly-PseAAC significantly. A matlab software package for CKSAAP_PhoglySite can be freely downloaded from https://github.cornijuzhe1120/Matlab_Software/blob/master/CKSAAP_PhoglySite_Matlab_Software.zip. (C) 2016 Elsevier Ltd. All rights reserved.