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An Analysis of Ortholog Clusters Detected from Multiple Genomes  

Kim, Sun-Shin (국립보건연구원)
Oh, Jeong-Su (국가생물자원정보관리센터)
Lee, Bum-Ju (충북대학교 전자계산학)
Kim, Tae-Kyung (충북대학교 정보산업공학)
Jung, Kwang-Su (충북대학교 전자계산학)
Rhee, Chung-Sei (충북대학교 전기전자컴퓨터공학)
Kim, Young-Chang (충북대학교 생명과학)
Cho, Wan-Sup (충북대학교 경영정보학)
Ryu, Keun-Ho (충북대학교 전기전자컴퓨터공학)
Publication Information
Journal of KIISE:Databases / v.35, no.2, 2008 , pp. 125-131 More about this Journal
Abstract
It is very useful to predict orthologs for new genome annotation and research on genome evolution. We showed that the previous work can be extended to construct OCs(Ortholog Clusters) automatically from multiple complete-genomes. The proposed method also has the quality of production of InParanoid, which produces orthologs from just two genomes. On the other hand, in order to predict more exactly the function of a newly sequenced gene it can be an important issue to prevent unwanted inclusion of paralogs into the OCs. We have, here, investigated how well it is possible to construct a functionally purer OCs with score cut-offs. Our OCs were generated from the datasets of 20 procaryotes. The similarity with both COG(Clusters of Orthologous Group) and KO(Kegg Orthology) against our OCs has about 90% and inclines to increase with the growth of score cut-offs.
Keywords
ortholog; genome; InParanoid; paralog; COG and KO;
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