ArticleBMC bioinformatics2014
Improvement of domain-level ortholog clustering by optimizing domain-specific sum-of-pairs score.
Article in BMC bioinformatics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- eggNOG v7: phylogeny-based orthology predictions and functional annotations.Nucleic acids research · 2026Article
- 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
- Ten Years of Collaborative Progress in the Quest for Orthologs.Molecular biology and evolution · 2021Article
- The Quest for Orthologs benchmark service and consensus calls in 2020.Nucleic acids research · 2020Article
- MBGD update 2018: microbial genome database based on hierarchical orthology relations covering closely related and distantly related comparisons.Nucleic acids research · 2019Article
- Inferring Orthologs: Open Questions and Perspectives.Genomics insights · 2016Review
- Construction of an ortholog database using the semantic web technology for integrative analysis of genomic data.PloS one · 2015Article
- MBGD update 2015: microbial genome database for flexible ortholog analysis utilizing a diverse set of genomic data.Nucleic acids research · 2015Article
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2 authors.
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Abstract
backgroundIdentification of ortholog groups is a crucial step in comparative analysis of multiple genomes. Although several computational methods have been developed to create ortholog groups, most of those methods do not evaluate orthology at the sub-gene level. In our method for domain-level ortholog clustering, DomClust, proteins are split into domains on the basis of alignment boundaries identified by all-against-all pairwise comparison, but it often fails to determine appropriate boundaries.
resultsWe developed a method to improve domain-level ortholog classification using multiple alignment information. This method is based on a scoring scheme, the domain-specific sum-of-pairs (DSP) score, which evaluates ortholog clustering results at the domain level as the sum total of domain-level alignment scores. We developed a refinement pipeline to improve domain-level clustering, DomRefine, by optimizing the DSP score. We applied DomRefine to domain-level ortholog groups created by DomClust using a dataset obtained from the Microbial Genome Database for Comparative Analysis (MBGD), and evaluated the results using COG clusters and TIGRFAMs models as the reference data. Thus, we observed that the agreement between the resulting classification and the classifications in the reference databases is improved at almost every step in the refinement pipeline. Moreover, the refined classification showed better agreement than the classifications in the eggNOG databases when TIGRFAMs was used as the reference database.
conclusionsDomRefine is a useful tool for improving the quality of domain-level ortholog classification among microbial genomes. Combining with a rapid domain-level ortholog clustering method, such as DomClust, it can be used to create a high-quality ortholog database that can serve as a solid basis for various comparative genome analyses.
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