PROTEIN STRUCTURE PREDICTION USING SUPPORT VECTOR MACHINE

PROTEIN STRUCTURE PREDICTION USING SUPPORT VECTOR MACHINE

Anil Kumar Mandle1, Pranita Jain2, and Shailendra Kumar Shrivastava3

1Research Scholar, Information Technology Department Samrat Ashok Technological InstituteVidisha, (M. P.) INDIA

2Astt.Prof. Information Technology Department Samrat Ashok Technological Institute Vidisha, (M. P.) INDIA

3HOD, Information Technology Department Samrat Ashok Technological Institute Vidisha, (M. P.) INDIA

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.

KEYWORDS

Bioinformatics, Support Vector Machine, protein folding, protein structure prediction.

Open source URL : http://airccse.org/journal/ijsc/papers/2112ijsc06.pdf

http://airccse.org/journal/ijsc/current2012.html