Nucleic Acids Research Advance Access originally published online on December 14, 2006
Nucleic Acids Research 2007 35(2):540-549; doi:10.1093/nar/gkl1083
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Nucleic Acids Research, 2007, Vol. 35, No. 2 540-549
© 2006 The Author(s).
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Genomics |
GISMOgene identification using a support vector machine for ORF classification
Center for Biotechnology, Bielefeld University (CeBiTec) D-33594 Bielefeld, Germany 1 Bioinformatics and Pattern Discovery Group, IBM T.J. Watson Research Center Yorktown Heights, NY 10598, USA 2 Mathematics and Computer Science Division, Argonne National Laboratory Argonne, IL 60439, USA
*To whom correspondence should be addressed. Tel: +49 521 106 4823; Fax: +49 521 106 6419; Email: lutz.krause{at}cebitec.uni-bielefeld.de
Received September 4, 2006. Revised November 22, 2006. Accepted November 24, 2006.
We present the novel prokaryotic gene finder GISMO, which combines searches for protein family domains with composition-based classification based on a support vector machine. GISMO is highly accurate; exhibiting high sensitivity and specificity in gene identification. We found that it performs well for complete prokaryotic chromosomes, irrespective of their GC content, and also for plasmids as short as 10 kb, short genes and for genes with atypical sequence composition. Using GISMO, we found several thousand new predictions for the published genomes that are supported by extrinsic evidence, which strongly suggest that these are very likely biologically active genes. The source code for GISMO is freely available under the GPL license.
The authors wish it to be known that, in their opinion, the first two authors should be regarded as joint First Authors
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