ArticleBMC systems biology2012
BBH-LS: an algorithm for computing positional homologs using sequence and gene context similarity.
Article in BMC systems biology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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10 citing papers in PubMed.
- Quantifying the Influence of Genetic Context on Duplicated Mammalian Genes.Molecular biology and evolution · 2026Article
- Quantifying the influence of genetic context on duplicated mammalian genes.bioRxiv : the preprint server for biology · 2025Article
- A new cancer/testis long noncoding RNA, the OTP-AS1 RNA.Scientific reports · 2024Article
- Orthonome - a new pipeline for predicting high quality orthologue gene sets applicable to complete and draft genomes.BMC genomics · 2017Article
- Altered expression profiles of microRNA families during de-etiolation of maize and rice leaves.BMC research notes · 2017Article
- Systems analysis of cis-regulatory motifs in C4 photosynthesis genes using maize and rice leaf transcriptomic data during a process of de-etiolation.Journal of experimental botany · 2016Article
- PoplarGene: poplar gene network and resource for mining functional information for genes from woody plants.Scientific reports · 2016Article
- Comparative analyses of C₄ and C₃ photosynthesis in developing leaves of maize and rice.Nature biotechnology · 2014Article
- Stringent homology-based prediction of H. sapiens-M. tuberculosis H37Rv protein-protein interactions.Biology direct · 2014Article
- Antimicrobial peptides design by evolutionary multiobjective optimization.PLoS computational biology · 2013Article
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2 authors.
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Abstract
backgroundIdentifying corresponding genes (orthologs) in different species is an important step in genome-wide comparative analysis. In particular, one-to-one correspondences between genes in different species greatly simplify certain problems such as transfer of function annotation and genome rearrangement studies. Positional homologs are the direct descendants of a single ancestral gene in the most recent common ancestor and by definition form one-to-one correspondence.
resultsIn this work, we present a simple yet effective method (BBH-LS) for the identification of positional homologs from the comparative analysis of two genomes. Our BBH-LS method integrates sequence similarity and gene context similarity in order to get more accurate ortholog assignments. Specifically, BBH-LS applies the bidirectional best hit heuristic to a combination of sequence similarity and gene context similarity scores.
conclusionWe applied our method to the human, mouse, and rat genomes and found that BBH-LS produced the best results when using both sequence and gene context information equally. Compared to the state-of-the-art algorithms, such as MSOAR2, BBH-LS is able to identify more positional homologs with fewer false positives.
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