Proteins domain classification and prediction from protein second | 22587
Journal of Proteomics & Bioinformatics

Journal of Proteomics & Bioinformatics
Open Access

ISSN: 0974-276X

+44 1223 790975

Proteins domain classification and prediction from protein secondary structure

3rd International Conference on Proteomics & Bioinformatics

July 15-17, 2013 Courtyard by Marriott Philadelphia Downtown, USA

Habes Alkhraisat

Scientific Tracks Abstracts: J Proteomics Bioinform

Abstract :

Prediction of protein function is of significance in studying biological processes. The prediction of protein function is one of the most demanding tasks in the study of bioinformatics. One approach for function prediction is to classify a protein into functional family. Classification of protein structures helps to understand relationships between protein structure and function. Machine learning methods greatly help to improve the classification of protein function. This paper presents a method for classifying the proteins based on the secondary structure. Support vector machine (SVM) is a useful method for such classification, which may involve proteins with diverse sequence distribution. We have developed SVM classification of a protein into functional domains from its secondary structure.

Biography :

Habes M. Alkhraisat is Assistant Professor of Computer Science in the Department of Computer Science at the Al-Balqa Applied University. He received his BA from Al-Balqa Applied University in 2001, master degree of computer science from University of Jordan in 2003, and a Ph.D. from Saint Petersburg Electro Technical University in 2008.