ArticleNucleic acids research2006
Hierarchical clustering algorithm for comprehensive orthologous-domain classification in multiple genomes.
Article in Nucleic acids research, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers.
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43 citing papers in PubMed.
- Reconstructing Evolutionary Histories with Hierarchical Orthologous Groups.Journal of molecular evolution · 2025Review
- Towards molecular evolutionary epigenomics with an expanded nucleotide code involving methylated bases.DNA research : an international journal for rapid publication of reports on genes and genomes · 2025Article
- Clustering biological sequences with dynamic sequence similarity threshold.BMC bioinformatics · 2022Article
- Ten Years of Collaborative Progress in the Quest for Orthologs.Molecular biology and evolution · 2021Article
- The physiological potential of anammox bacteria as revealed by their core genome structure.DNA research : an international journal for rapid publication of reports on genes and genomes · 2021Article
- Predicting DNA binding protein-drug interactions based on network similarity.BMC bioinformatics · 2020Article
- The power of cooperation: Experimental and computational approaches in the functional characterization of bacterial sRNAs.Molecular microbiology · 2020Review
- Contents, Construction Methods, Data Resources, and Functions Comparative Analysis of Bacteria Databases.International journal of biological sciences · 2020Review
- MBGD update 2018: microbial genome database based on hierarchical orthology relations covering closely related and distantly related comparisons.Nucleic acids research · 2019Article
- RNA-Seq Analysis Reveals Genes Related to Photoreception, Nutrient Uptake, and Toxicity in a Noxious Red-Tide RaphidophyteFrontiers in microbiology · 2019Article
- ClustAGE: a tool for clustering and distribution analysis of bacterial accessory genomic elements.BMC bioinformatics · 2018Article
- Automatic identification of optimal marker genes for phenotypic and taxonomic groups of microorganisms.PloS one · 2018Article
- An acid-tolerant ammonia-oxidizing γ-proteobacterium from soil.The ISME journal · 2017Article
- Complete genome sequence and expression profile of the commercial lytic enzyme producer Lysobacter enzymogenes M497-1.DNA research : an international journal for rapid publication of reports on genes and genomes · 2017Article
- Genome-wide survey of codons under diversifying selection in a highly recombining bacterial species, Helicobacter pylori.DNA research : an international journal for rapid publication of reports on genes and genomes · 2016Article
- Ortholog-Finder: A Tool for Constructing an Ortholog Data Set.Genome biology and evolution · 2016Article
- A Novel Approach to Helicobacter pylori Pan-Genome Analysis for Identification of Genomic Islands.PloS one · 2016Article
- Complete genome and gene expression analyses of Asaia bogorensis reveal unique responses to culture with mammalian cells as a potential opportunistic human pathogen.DNA research : an international journal for rapid publication of reports on genes and genomes · 2015Article
- MBGD update 2015: microbial genome database for flexible ortholog analysis utilizing a diverse set of genomic data.Nucleic acids research · 2015Article
- Construction of an ortholog database using the semantic web technology for integrative analysis of genomic data.PloS one · 2015Article
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1 author.
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Abstract
Ortholog identification is a crucial first step in comparative genomics. Here, we present a rapid method of ortholog grouping which is effective enough to allow the comparison of many genomes simultaneously. The method takes as input all-against-all similarity data and classifies genes based on the traditional hierarchical clustering algorithm UPGMA. In the course of clustering, the method detects domain fusion or fission events, and splits clusters into domains if required. The subsequent procedure splits the resulting trees such that intra-species paralogous genes are divided into different groups so as to create plausible orthologous groups. As a result, the procedure can split genes into the domains minimally required for ortholog grouping. The procedure, named DomClust, was tested using the COG database as a reference. When comparing several clustering algorithms combined with the conventional bidirectional best-hit (BBH) criterion, we found that our method generally showed better agreement with the COG classification. By comparing the clustering results generated from datasets of different releases, we also found that our method showed relatively good stability in comparison to the BBH-based methods.
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