An algorithm for hierarchical classification of genes of prokaryotic genomes

  • Authors:

  • Hongwei Wu;Fenglou Mao;Victor Olman;Ying Xu

  • Affiliations:

  • Computational Systems Biology Laboratory, Department of Biochemistry and Molecular Biology and Institute of Bioinformatics, University of Georgia, Athens, GA;Computational Systems Biology Laboratory, Department of Biochemistry and Molecular Biology and Institute of Bioinformatics, University of Georgia, Athens, GA;Computational Systems Biology Laboratory, Department of Biochemistry and Molecular Biology and Institute of Bioinformatics, University of Georgia, Athens, GA;Computational Systems Biology Laboratory, Department of Biochemistry and Molecular Biology and Institute of Bioinformatics, University of Georgia, Athens, GA

  • Venue:
  • ISBRA'07 Proceedings of the 3rd international conference on Bioinformatics research and applications
  • Year:
  • 2007

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Abstract

We present in this paper our hierarchical classification of genes for prokaryotic genomes from a methodological point of view. Our classification scheme is unique in that (1) the functional equivalence relationships among genes are assessed by using both sequence similarity and genomic context information, (2) genes are grouped into clusters of multiple resolution levels based on their equivalence relationships among each other, and (3) gene clusters, which are either parallel-to or inside-of one another, naturally form a hierarchical structure. This classification scheme has been applied for the genes of 224 complete prokaryotic genomes (release as of March, 2005). The classification results are available at http://csbl.bmb.uga.edu/HCG, and are validated through comparisons with the taxonomy of these 224 genomes, and with two existing gene classification schemes, Clusters of Orthologous Groups of proteins (COG) and Pfam, respectively.