Journal article
PSSM-Suc: Accurately predicting succinylation using position specific scoring matrix into bigram for feature extraction
Journal of theoretical biology, Vol.425, pp.97-102
07/21/2017
DOI: 10.1016/j.jtbi.2017.05.005
PMID: 28483566
Abstract
•New computational approach for predicting succinylation sites.•Remarkable transformation of the position specific scoring matrix into bigram.•Evolutionary information collected in bigram probabilities for accurate prediction.
Post-translational modification (PTM) is a covalent and enzymatic modification of proteins, which contributes to diversify the proteome. Despite many reported PTMs with essential roles in cellular functioning, lysine succinylation has emerged as a subject of particular interest. Because its experimental identification remains a costly and time-consuming process, computational predictors have been recently proposed for tackling this important issue. However, the performance of current predictors is still very limited. In this paper, we propose a new predictor called PSSM-Suc which employs evolutionary information of amino acids for predicting succinylated lysine residues. Here we described each lysine residue in terms of profile bigrams extracted from position specific scoring matrices. We compared the performance of PSSM-Suc to that of existing predictors using a widely used benchmark dataset. PSSM-Suc showed a significant improvement in performance over state-of-the-art predictors. Its sensitivity, accuracy and Matthews correlation coefficient were 0.8159, 0.8199 and 0.6396, respectively.
Details
- Title: Subtitle
- PSSM-Suc: Accurately predicting succinylation using position specific scoring matrix into bigram for feature extraction
- Creators
- Abdollah Dehzangi - Department of Psychiatry, Carver College of Medicine, University of Iowa, Iowa, USAYosvany López - Department of Medical Science Mathematics, Medical Research Institute, Tokyo Medical and Dental University, Tokyo, JapanSunil Pranit Lal - School of Engineering & Advanced Technology, Massey University, New ZealandGhazaleh Taherzadeh - School of Information and Communication Technology, Griffith University, Parklands Drive, Southport, Queensland 4215, AustraliaJacob Michaelson - Department of Psychiatry, Carver College of Medicine, University of Iowa, Iowa, USAAbdul Sattar - School of Information and Communication Technology, Griffith University, Parklands Drive, Southport, Queensland 4215, AustraliaTatsuhiko Tsunoda - Department of Medical Science Mathematics, Medical Research Institute, Tokyo Medical and Dental University, Tokyo, JapanAlok Sharma - Laboratory for Medical Science Mathematics, RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
- Resource Type
- Journal article
- Publication Details
- Journal of theoretical biology, Vol.425, pp.97-102
- Publisher
- Elsevier Ltd
- DOI
- 10.1016/j.jtbi.2017.05.005
- PMID
- 28483566
- ISSN
- 0022-5193
- eISSN
- 1095-8541
- Language
- English
- Date published
- 07/21/2017
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Communication Sciences and Disorders; Psychiatry; Iowa Neuroscience Institute
- Record Identifier
- 9984070680302771
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