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Gene prediction using the Self-Organizing Map: automatic generation of multiple gene models

ARAN - Access to Research at NUI Galway

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dc.contributor.author McInerney, James O en
dc.contributor.author Smith, Terry J. en
dc.contributor.author Mahony, Shaun en
dc.contributor.author Golden, Aaron en
dc.date.accessioned 2009-02-06T16:26:47Z en
dc.date.available 2009-02-06T16:26:47Z en
dc.date.issued 2005-03-05 en
dc.identifier.citation Mahony, S. McInerney, J.O., Smith, T.J., Golden, A. (2004). Gene prediction using the Self-Organizing Map: automatic generation of multiple gene models. BMC Bioinformatics 2004, 5:23-32. en
dc.identifier.isbn 1471-2105 en
dc.identifier.uri http://hdl.handle.net/10379/103 en
dc.description.abstract Background: Many current gene prediction methods use only one model to represent protein-coding regions in a genome, and so are less likely to predict the location of genes that have an atypical sequence composition. It is likely that future improvements in gene finding will involve the development of methods that can adequately deal with intra-genomic compositional variation. Results: This work explores a new approach to gene-prediction, based on the Self-Organizing Map, which has the ability to automatically identify multiple gene models within a genome. The current implementation, named RescueNet, uses relative synonymous codon usage as the indicator of protein-coding potential. Conclusions: While its raw accuracy rate can be less than other methods, RescueNet consistently identifies some genes that other methods do not, and should therefore be of interest to gene-prediction software developers and genome annotation teams alike. RescueNet is recommended for use in conjunction with, or as a complement to, other gene prediction methods. en
dc.format application/pdf en
dc.language.iso en en
dc.publisher BioMed Central en
dc.subject Horizontally Transferred Genes en
dc.subject Synonymous Codon Usage en
dc.subject Complete Genome Sequence en
dc.subject Selection en
dc.subject Annotation en
dc.subject Bacterial Genome en
dc.subject Borrelia-Burgdorferi en
dc.subject Base Composition en
dc.subject Arabidopsis en
dc.subject Identification en
dc.subject.lcsh Arabidopsis en
dc.subject.lcsh Bacterial genomes en
dc.subject.lcsh Bacterial genetics en
dc.subject.lcsh Genomes en
dc.subject.lcsh Identification en
dc.title Gene prediction using the Self-Organizing Map: automatic generation of multiple gene models en
dc.type Article en

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