ArticleBMC genomics2014
A meta-approach for improving the prediction and the functional annotation of ortholog groups.
Article in BMC genomics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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13 citing papers in PubMed.
- Review
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- Genome-wide inference of the Camponotus floridanus protein-protein interaction network using homologous mapping and interacting domain profile pairs.Scientific reports · 2020Article
- Advances and Applications in the Quest for Orthologs.Molecular biology and evolution · 2019Article
- Multilevel comparative bioinformatics to investigate evolutionary relationships and specificities in gene annotations: an example for tomato and grapevine.BMC bioinformatics · 2018Article
- OrthoList 2: A New Comparative Genomic Analysis of Human andGenetics · 2018Article
- Meta-Analysis ofToxics · 2018Article
- Gearing up to handle the mosaic nature of life in the quest for orthologs.Bioinformatics (Oxford, England) · 2018Article
- Proximity ligation scaffolding and comparison of twoBiotechnology for biofuels · 2017Article
- WORMHOLE: Novel Least Diverged Ortholog Prediction through Machine Learning.PLoS computational biology · 2016Article
- Functional Annotations of Paralogs: A Blessing and a Curse.Life (Basel, Switzerland) · 2016Article
- Towards Consensus Gene Ages.Genome biology and evolution · 2016Article
- MTHFR Gene Polymorphism-Mutations and Air Pollution as Risk Factors for Breast Cancer: A Metaprediction Study.Nursing researchArticle
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3 authors.
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Abstract
backgroundIn comparative genomics, orthologs are used to transfer annotation from genes already characterized to newly sequenced genomes. Many methods have been developed for finding orthologs in sets of genomes. However, the application of different methods on the same proteome set can lead to distinct orthology predictions.
methodsWe developed a method based on a meta-approach that is able to combine the results of several methods for orthologous group prediction. The purpose of this method is to produce better quality results by using the overlapping results obtained from several individual orthologous gene prediction procedures. Our method proceeds in two steps. The first aims to construct seeds for groups of orthologous genes; these seeds correspond to the exact overlaps between the results of all or several methods. In the second step, these seed groups are expanded by using HMM profiles.
resultsWe evaluated our method on two standard reference benchmarks, OrthoBench and Orthology Benchmark Service. Our method presents a higher level of accurately predicted groups than the individual input methods of orthologous group prediction. Moreover, our method increases the number of annotated orthologous pairs without decreasing the annotation quality compared to twelve state-of-the-art methods.
conclusionsThe meta-approach based method appears to be a reliable procedure for predicting orthologous groups. Since a large number of methods for predicting groups of orthologous genes exist, it is quite conceivable to apply this meta-approach to several combinations of different methods.
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