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PMID: 16434444 Published · ppublish English Journal Article Research Support, N.I.H., Intramural

COCO-CL: hierarchical clustering of homology relations based on evolutionary correlations.

Bioinformatics (Oxford, England) ·Vol. 22 ·No. 7 ·2006-04-01 ·Pages 779-88

Jothi R, Zotenko E, Tasneem A, Przytycka TM

Abstract

Determining orthology relations among genes across multiple genomes is an important problem in the post-genomic era. Identifying orthologous genes can not only help predict functional annotations for newly sequenced or poorly characterized genomes, but can also help predict new protein-protein interactions. Unfortunately, determining orthology relation through computational methods is not straightforward due to the presence of paralogs. Traditional approaches have relied on pairwise sequence comparisons to construct graphs, which were then partitioned into putative clusters of orthologous groups. These methods do not attempt to preserve the non-transitivity and hierarchic nature of the orthology relation. We propose a new method, COCO-CL, for hierarchical clustering of homology relations and identification of orthologous groups of genes. Unlike previous approaches, which are based on pairwise sequence comparisons, our method explores the correlation of evolutionary histories of individual genes in a more global context. COCO-CL can be used as a semi-independent method to delineate the orthology/paralogy relation for a refined set of homologous proteins obtained using a less-conservative clustering approach, or as a refiner that removes putative out-paralogs from clusters computed using a more inclusive approach. We analyze our clustering results manually, with support from literature and functional annotations. Since our orthology determination procedure does not employ a species tree to infer duplication events, it can be used in situations when the species tree is unknown or uncertain. jothi@mail.nih.gov, przytyck@mail.nih.gov Supplementary materials are available at Bioinformatics online.

MeSH Terms
Algorithms Animals Cluster Analysis Computational Biology DNA-Directed RNA Polymerases/genetics Evolution, Molecular Glutamate-tRNA Ligase/genetics Humans Models, Biological Models, Genetic Phylogeny Protein Subunits/genetics Ribonuclease H/genetics Sequence Homology Serine Endopeptidases/genetics
Chemicals
Protein Subunits DNA-Directed RNA Polymerases Ribonuclease H Serine Endopeptidases Glutamate-tRNA Ligase
Authors & Affiliations
4 authors, click to expand affiliations / ORCID
Jothi Raja
National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA. jothi@mail.nih.gov
Zotenko Elena
Tasneem Asba
Przytycka Teresa M
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Article Info
Journal
Bioinformatics (Oxford, England)
Abbr.
Bioinformatics
ISSN
1367-4803
Published
2006-04-01
Epub
2006-00-24
Pages
779-88
Language
English
Region
England
NLM ID
9808944
PMCID
PMC1620014
Subset
IM
Grants
Intramural NIH HHS · United States
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