Volume 11 Number 8 (Aug. 2016)
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JSW 2016 Vol.11(8): 756-767 ISSN: 1796-217X
doi: 10.17706/jsw.11.8.756-767

Protein Fold Recognition Using Genetic Algorithm Optimized Voting Scheme and Profile Bigram

Harsh Saini1*, Gaurav Raicar1, Sunil Lal1, Abdollah Dehzangi2, Seiya Imoto3, Alok Sharma1,2
1The University of the South Pacific, Fiji.
2Griffith University, Brisbane, Australia.
3University of Tokyo, Japan.

Abstract—In biology, identifying the tertiary structure of a protein helps determine its functions. A step towards tertiary structure identification is predicting a protein’s fold. Computational methods have been applied to determine a protein’s fold by assembling information from its structural, physicochemical and/or evolutionary properties. It has been shown that evolutionary information helps improve prediction accuracy. In this study, a scheme is proposed that uses the genetic algorithm (GA) to optimize a weighted voting scheme to improve protein fold recognition. This scheme incorporates k-separated bigram transition probabilities for feature extraction, which are based on the Position Specific Scoring Matrix (PSSM). A set of SVM classifiers are used for initial classification, whereupon their predictions are consolidated using the optimized weighted voting scheme. This scheme has been demonstrated on the Ding and Dubchak (DD), Extended Ding and Dubchak (EDD) and Taguchi and Gromhia (TG) datasets benchmarked data sets.

Index Terms—K-separated bigrams, protein fold recognition, SCOP, PSSM, genetic algorithm, support vector machines.

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Cite: Harsh Saini, Gaurav Raicar, Sunil Lal, Abdollah Dehzangi, Seiya Imoto, Alok Sharma, "Protein Fold Recognition Using Genetic Algorithm Optimized Voting Scheme and Profile Bigram," Journal of Software vol. 11, no. 8, pp. 756-767, 2016.

General Information

ISSN: 1796-217X (Online)
Frequency:  Bimonthly (Since 2020)
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, Google Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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