ArticleBMC bioinformatics2010
Enrichment of homologs in insignificant BLAST hits by co-complex network alignment.
Article in BMC bioinformatics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Protein functional annotation of simultaneously improved stability, accuracy and false discovery rate achieved by a sequence-based deep learning.Briefings in bioinformatics · 2020Article
- Extensive gene remodeling in the viral world: new evidence for nongradual evolution in the mobilome network.Genome biology and evolution · 2014Article
- Phylometrics: a pipeline for inferring phylogenetic trees from a sequence relationship network perspective.BMC bioinformatics · 2010Article
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4 authors.
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Abstract
backgroundHomology is a crucial concept in comparative genomics. The algorithm probably most widely used for homology detection in comparative genomics, is BLAST. Usually a stringent score cutoff is applied to distinguish putative homologs from possible false positive hits. As a consequence, some BLAST hits are discarded that are in fact homologous.
resultsAnalogous to the use of the genomics context in genome alignments, we test whether conserved functional context can be used to select candidate homologs from insignificant BLAST hits. We make a co-complex network alignment between complex subunits in yeast and human and find that proteins with an insignificant BLAST hit that are part of homologous complexes, are likely to be homologous themselves. Further analysis of the distant homologs we recovered using the co-complex network alignment, shows that a large majority of these distant homologs are in fact ancient paralogs.
conclusionsOur results show that, even though evolution takes place at the sequence and genome level, co-complex networks can be used as circumstantial evidence to improve confidence in the homology of distantly related sequences.
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