TY - JOUR
T1 - Gene prediction using the Self-Organizing Map
T2 - Automatic generation of multiple gene models
AU - Mahony, Shaun
AU - McInerney, James O.
AU - Smith, Terry J.
AU - Golden, Aaron
PY - 2004/3/5
Y1 - 2004/3/5
N2 - 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 geneprediction software developers and genome annotation teams alike. RescueNet is recommended for use in conjunction with, or as a complement to, other gene prediction methods.
AB - 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 geneprediction software developers and genome annotation teams alike. RescueNet is recommended for use in conjunction with, or as a complement to, other gene prediction methods.
UR - http://www.scopus.com/inward/record.url?scp=2942542784&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=2942542784&partnerID=8YFLogxK
U2 - 10.1186/1471-2105-5-23
DO - 10.1186/1471-2105-5-23
M3 - Article
C2 - 15070404
AN - SCOPUS:2942542784
SN - 1471-2105
VL - 5
JO - BMC bioinformatics
JF - BMC bioinformatics
M1 - 23
ER -