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Prediction of protein homo-oligomer types with a novel approach of glide zoom window feature extraction

  • Northwestern Polytechnical University Xian

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

A novel approach of glide zoom window feature extraction based on protein sequence was proposed for predicting protein homo-oligomers. Based on the concept of glide zoom window, three feature vectors of amino acids distance sum, amino acids mean distance and amino acids distribution, were extracted. A series of feature sets were constructed by combing these feature vectors with amino acids composition to form pseudo amino acid compositions (PseAAC). The support vector machine (SVM) was used as base classifier. The 73.19% total accuracy is arrived in jackknife test, which is 7.87% higher than that of conventional amino acid composition method. The results show that the novel feature extraction method of glide zoom window is effective and feasible, and the feature vectors extracted with this method may contain more protein structure information.

Original languageEnglish
Title of host publicationAdvanced Intelligent Computing Theories and Applications
Subtitle of host publicationWith Aspects of Theoretical and Methodological Issues - 4th International Conference on Intelligent Computing, ICIC 2008, Proceedings
Pages71-78
Number of pages8
DOIs
StatePublished - 2008
Event4th International Conference on Intelligent Computing, ICIC 2008 - Shanghai, China
Duration: 15 Sep 200818 Sep 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5226 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference4th International Conference on Intelligent Computing, ICIC 2008
Country/TerritoryChina
CityShanghai
Period15/09/0818/09/08

Keywords

  • Feature Extraction
  • Glide Zoom Window
  • Homo-oligomer
  • Pseudo Amino Acid Compositions
  • Support Vector Machine

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