An improvement method based on OrthoMCL by adding the domain information

Xinyu Que*, Fa Zhang, Shengzhong Feng, Bo Yuan, Zhiyong Liu

*Corresponding author for this work

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

Abstract

Existing clustering methods have so far not separated paralogs from orthologs effectively. Since proteins evolve with their structural and functional domains as independent units, to achieve a higher level of sensitivity and specificity in assessing the similarity, it is necessary to add the domain information. We presented a method to improve the clustering results of the orthologs and paralogs from multiple species by adding the domain information. First, we do the all-against-all blast between the protein sequences. At the same time, we make the blast between the sequences and Pfam-A database to find which of the sequences share the same domain. Then we use this information as an additional criterion for filtering false relationships in all-against-all BLASTP results, and generate a similarity matrix. Final, the MCL algorithm is applied to group orthologs from multiple species. Our preliminary results show that our method can improve strikingly the precision of sequence clustering.

Original languageEnglish
Title of host publicationProceedings of the 2008 International Conference on Bioinformatics and Computational Biology, BIOCOMP 2008
Pages418-423
Number of pages6
Publication statusPublished - 2008
Externally publishedYes
Event2008 International Conference on Bioinformatics and Computational Biology, BIOCOMP 2008 - Las Vegas, NV, United States
Duration: 14 Jul 200817 Jul 2008

Publication series

NameProceedings of the 2008 International Conference on Bioinformatics and Computational Biology, BIOCOMP 2008

Conference

Conference2008 International Conference on Bioinformatics and Computational Biology, BIOCOMP 2008
Country/TerritoryUnited States
CityLas Vegas, NV
Period14/07/0817/07/08

Keywords

  • Clustering
  • Domain
  • Ortholog
  • Paralog
  • Sequence similarity

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