title: Accurate prediction of orthologous gene groups in microbes.
abstract: We present a new computational method for the prediction of orthologous gene groups for microbial genomes based on the prediction of co-occurrences of homologous genes. The method is inspired by the observation that homologous genes are highly likely to be orthologous if their neighboring genes are also homologous. Based on co-occurrences of homologous genes, we have grouped the (predicted) operons of 77 selected sequenced microbial genomes so that operons of the same group are highly likely to be functionally similar or related. We then cluster the homologous genes in the same operon group so that genes of the same cluster are highly likely to be similar in terms of their sequences and functions, i.e., they are predicted to be orthologous genes. By comparing our predicted orthologous gene groups with the COG assignments and NCBI annotations, we conclude that our method is promising to provide more accurate and specific predictions than the existing methods.
authors.affiliation: Department of Biochemistry and Molecular Biology and Institute of Bioinformatics, University of Georgia, Athens, GA 30622, USA. hongweiw@csbl.bmb.uga.edu
authors.forename: Hongwei
authors.initials: H
authors.lastname: Wu
authors.forename: Fenglou
authors.initials: F
authors.lastname: Mao
authors.forename: Victor
authors.initials: V
authors.lastname: Olman
authors.forename: Ying
authors.initials: Y
authors.lastname: Xu
mesh_terms: D000465:Algorithms; D001483:Base Sequence; D002874:Chromosome Mapping / Q000379:methods*; D016680:Genome, Bacterial / Q000235:genetics*; D008969:Molecular Sequence Data; D005810:Multigene Family / Q000235:genetics*; D016415:Sequence Alignment / Q000379:methods*; D017422:Sequence Analysis, DNA / Q000379:methods*; D012689:Sequence Homology, Nucleic Acid