A method of precise mRNA/DNA homology-based gene structure prediction.
BACKGROUND
Accurate and automatic gene finding and structural prediction is a common problem in bioinformatics, and applications need to be capable of handling non-canonical splice sites, micro-exons and partial gene structure predictions that span across several genomic clones.


RESULTS
We present a mRNA/DNA homology based gene structure prediction tool, GIGOgene. We use a new affine gap penalty splice-enhanced global alignment algorithm running in linear memory for a high quality annotation of splice sites. Our tool includes a novel algorithm to assemble partial gene structure predictions using interval graphs. GIGOgene exhibited a sensitivity of 99.08% and a specificity of 99.98% on the Genie learning set, and demonstrated a higher quality of gene structural prediction when compared to Sim4, est2genome, Spidey, Galahad and BLAT, including when genes contained micro-exons and non-canonical splice sites. GIGOgene showed an acceptable loss of prediction quality when confronted with a noisy Genie learning set simulating ESTs.


CONCLUSIONS
GIGOgene shows a higher quality of gene structure prediction for mRNA/DNA spliced alignment when compared to other available tools.
Churbanov
Alexander
A
Department of Computer Science, College of Information Science and Technology, University of Nebraska, Omaha, NE 68182-0116, USA. achurbanov@mail.unomaha.edu
Pauley
Mark
M
Quest
Daniel
D
Ali
Hesham
H
D000465:Algorithms; D002999:Clone Cells / Q000737:chemistry; D004247:DNA / Q000737:chemistry*; D011237:Predictive Value of Tests; D012333:RNA, Messenger / Q000737:chemistry*; D016415:Sequence Alignment; D012689:Sequence Homology, Nucleic Acid; D012984:Software
D012333:RNA, Messenger; D004247:DNA