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Protein Domains Prediction Method Based on Support Vector Machines

ZOU Shuxue1, HUANG Yanxin1, LI Yanwen2, ZHOU Chunguang1   

  1. 1. College of Computer Science and Technology, Jilin University, Changchun 130012, China;2. School of Computer Science, Northeast Normal University, Changchun 130024, China
  • Received:2008-02-29 Revised:1900-01-01 Online:2008-09-26 Published:2008-09-26
  • Contact: ZHOU Chunguang

Abstract: Guessing the boundaries of structural domains has been an important and challenging problem in experimentand computational structural biology. A promising method for detecting the domain structure of a protein from sequence information alone was presented. The method is based on analyzing multiple sequence alignments that are derived from a database search. Multiple measures were defined to quantify the domain information content of each position along the sequence and were combined into a single predictor using support vector machines. The overall accuracy of the method for a single protein chains dataset is about 85%. The result demonstrates that the utility of the method can help not only predict the complete 3D structure of a protein but also study proteins’ building blocks of functional analysis.

Key words: protein domains, sequence, support vector machine, bi oinformatics

CLC Number: 

  • TP391.4