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Protein Structure Prediction Using Support Vector Machine

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Author(s): Anil Kumar Mandle | Pranita Jain | Shailendra Kumar Shrivastava

Journal: International Journal on Soft Computing
ISSN 2229-7103

Volume: 3;
Issue: 1;
Start page: 67;
Date: 2012;
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Keywords: Bioinformatics | Support Vector Machine | protein folding | protein structure prediction

ABSTRACT
Support Vector Machine (SVM) is used for predict the protein structural. Bioinformatics method use to protein structure prediction mostly depends on the amino acid sequence. In this paper, work predicted of 1-D, 2-D, and 3-D protein structure prediction. Protein structure prediction is one of the most important problems in modern computation biology. Support Vector Machine haves shown strong generalization ability protein structure prediction. Binary classification techniques of Support Vector Machine are implemented and RBF kernel function is used in SVM. This Radial Basic Function (RBF) of SVM produces better accuracy in terms of classification and the learning results.

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