Protein remote homology detection using order profiles

Bin Liu*, Lei Lin, Xiaolong Wang, Xuan Wang

*Corresponding author for this work

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

2 Citations (Scopus)

Abstract

Protein remote homology detection is a central problem in bioinformatics. In this study, we present a novel building block of proteins called order profiles (OP) to use the evolutionary information of the protein sequence frequency profiles and apply this novel building block to remote homology detection. Order profiles contain the evolutionary information extracted from the protein sequence frequency profiles outputted by PSI-BLAST. The performance of our method is further improved by applying an efficient feature extraction algorithm from natural language processing, namely, latent semantic analysis (LSA). When tested on SCOP 1.53 benchmark, our method outperforms the other building-block-based methods and related methods.

Original languageEnglish
Title of host publicationProceedings - 2009 International Joint Conference on Bioinformatics, Systems Biology and Intelligent Computing, IJCBS 2009
Pages255-260
Number of pages6
DOIs
Publication statusPublished - 2009
Externally publishedYes
Event2009 International Joint Conference on Bioinformatics, Systems Biology and Intelligent Computing, IJCBS 2009 - Shanghai, China
Duration: 3 Aug 20095 Aug 2009

Publication series

NameProceedings - 2009 International Joint Conference on Bioinformatics, Systems Biology and Intelligent Computing, IJCBS 2009

Conference

Conference2009 International Joint Conference on Bioinformatics, Systems Biology and Intelligent Computing, IJCBS 2009
Country/TerritoryChina
CityShanghai
Period3/08/095/08/09

Keywords

  • Latent semantic analysis
  • Profiles
  • Remote homology detection
  • Support vector machine

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