ArticleGenome biology2006
Vertebrate gene finding from multiple-species alignments using a two-level strategy.
Article in Genome biology, 2006. 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, 15 citations in OpenAlex.
- Whole-Genome Alignment and Comparative Annotation.Annual review of animal biosciences · 2019Review
- Highly constrained intergenic Drosophila ultraconserved elements are candidate ncRNAs.Genome biology and evolution · 2015Article
- Coding sequence density estimation via topological pressure.Journal of mathematical biology · 2015Article
- Article
- Reranking candidate gene models with cross-species comparison for improved gene prediction.BMC bioinformatics · 2008Article
- Resolving the structural features of genomic islands: a machine learning approach.Genome research · 2008Article
- CONTRAST: a discriminative, phylogeny-free approach to multiple informant de novo gene prediction.Genome biology · 2007Article
- EGASP: the human ENCODE Genome Annotation Assessment Project.Genome biology · 2006Review
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
backgroundOne way in which the accuracy of gene structure prediction in vertebrate DNA sequences can be improved is by analyzing alignments with multiple related species, since functional regions of genes tend to be more conserved.
resultsWe describe DOGFISH, a vertebrate gene finder consisting of a cleanly separated site classifier and structure predictor. The classifier scores potential splice sites and other features, using sequence alignments between multiple vertebrate species, while the structure predictor hypothesizes coding transcripts by combining these scores using a simple model of gene structure. This also identifies and assigns confidence scores to possible additional exons. Performance is assessed on the ENCODE regions. We predict transcripts and exons across the whole human genome, and identify over 10,000 high confidence new coding exons not in the Ensembl gene set.
conclusionWe present a practical multiple species gene prediction method. Accuracy improves as additional species, up to at least eight, are introduced. The novel predictions of the whole-genome scan should support efficient experimental verification.
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