AI Article Synopsis
- The annotation process for the Arabidopsis thaliana genome faces challenges related to time and quality, necessitating the selection of effective tools for computer-assisted annotation.
- The new AraSet dataset has been created to assess multi-gene models, introducing innovative evaluation measures at both the protein and gene model levels, finding that GeneMark.hmm is the most accurate software for gene prediction.
- The AraSet resources and related programs are publicly accessible online, promoting their use in improving gene prediction methods across various eukaryotic genomes.
Article Abstract
Motivation: The annotation of the Arabidopsis thaliana genome remains a problem in terms of time and quality. To improve the annotation process, we want to choose the most appropriate tools to use inside a computer-assisted annotation platform. We therefore need evaluation of prediction programs with Arabidopsis sequences containing multiple genes.
Results: We have developed AraSet, a data set of contigs of validated genes, enabling the evaluation of multi-gene models for the Arabidopsis genome. Besides conventional metrics to evaluate gene prediction at the site and the exon levels, new measures were introduced for the prediction at the protein sequence level as well as for the evaluation of gene models. This evaluation method is of general interest and could apply to any new gene prediction software and to any eukaryotic genome. The GeneMark.hmm program appears to be the most accurate software at all three levels for the Arabidopsis genomic sequences. Gene modeling could be further improved by combination of prediction software.
Availability: The AraSet sequence set, the Perl programs and complementary results and notes are available at http://sphinx.rug.ac.be:8080/biocomp/napav/.
Contact: Pierre.Rouze@gengenp.rug.ac.be.
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| http://dx.doi.org/10.1093/bioinformatics/15.11.887 | DOI Listing |
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