title: predCar-site: Carbonylation sites prediction in proteins using support vector machine with resolving data imbalanced issue.
abstract: The carbonylation is found as an irreversible post-translational modification and considered a biomarker of oxidative stress. It plays major role not only in orchestrating various biological processes but also associated with some diseases such as Alzheimer's disease, diabetes, and Parkinson's disease. However, since the experimental technologies are costly and time-consuming to detect the carbonylation sites in proteins, an accurate computational method for predicting carbonylation sites is an urgent issue which can be useful for drug development. In this study, a novel computational tool termed predCar-Site has been developed to predict protein carbonylation sites by (1) incorporating the sequence-coupled information into the general pseudo amino acid composition, (2) balancing the effect of skewed training dataset by Different Error Costs method, and (3) constructing a predictor using support vector machine as classifier. This predCar-Site predictor achieves an average AUC (area under curve) score of 0.9959, 0.9999, 1, and 0.9997 in predicting the carbonylation sites of K, P, R, and T, respectively. All of the experimental results along with AUC are found from the average of 5 complete runs of the 10-fold cross-validation and those results indicate significantly better performance than existing predictors. A user-friendly web server of predCar-Site is available at http://research.ru.ac.bd/predCar-Site/.
authors.affiliation: Department of Computer Science & Engineering, University of Rajshahi, Bangladesh. Electronic address: mehedi_ru@yahoo.com.
authors.forename: Md Al Mehedi
authors.initials: MA
authors.lastname: Hasan
authors.affiliation: Advanced Analytics Institute and Centre for Health Technologies, University of Technology Sydney, Australia. Electronic address: Jinyan.Li@uts.edu.au.
authors.forename: Jinyan
authors.initials: J
authors.lastname: Li
authors.affiliation: Department of Computer Science & Engineering, University of Rajshahi, Bangladesh. Electronic address: shamim_cst@yahoo.com.
authors.forename: Shamim
authors.initials: S
authors.lastname: Ahmad
authors.affiliation: Department of Computer Science & Engineering, University of Rajshahi, Bangladesh. Electronic address: khademul.cse@ru.ac.bd.
authors.forename: Md Khademul Islam
authors.initials: MK
authors.lastname: Molla
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D006801:Humans; D008954:Models, Biological; D050050:Protein Carbonylation; D011499:Protein Processing, Post-Translational; D011506:Proteins / Q000737:chemistry*; D020539:Sequence Analysis, Protein / Q000379:methods*; D012984:Software; D060388:Support Vector Machine
chemical_list: D011506:Proteins
keywords: Carbonylation sites prediction; Data imbalance issue; Different error costs; General PseAAC; Sequence-coupling model; Support vector machine; predCar-site web-server