Automated generation of heuristics for biological sequence comparison.
BACKGROUND
Exhaustive methods of sequence alignment are accurate but slow, whereas heuristic approaches run quickly, but their complexity makes them more difficult to implement. We introduce bounded sparse dynamic programming (BSDP) to allow rapid approximation to exhaustive alignment. This is used within a framework whereby the alignment algorithms are described in terms of their underlying model, to allow automated development of efficient heuristic implementations which may be applied to a general set of sequence comparison problems.


RESULTS
The speed and accuracy of this approach compares favourably with existing methods. Examples of its use in the context of genome annotation are given.


CONCLUSIONS
This system allows rapid implementation of heuristics approximating to many complex alignment models, and has been incorporated into the freely available sequence alignment program, exonerate.
Slater
Guy St C
GS
The Ensembl Group, EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK. guy@ebi.ac.uk
Birney
Ewan
E
D000465:Algorithms; D001185:Artificial Intelligence; D001331:Automation; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D004247:DNA; D018076:DNA, Complementary / Q000378:metabolism; D016208:Databases, Factual; D016678:Genome; D006801:Humans; D016247:Information Storage and Retrieval; D008432:Mathematical Computing; D008954:Models, Biological; D008962:Models, Theoretical; D012333:RNA, Messenger / Q000378:metabolism; D016415:Sequence Alignment; D017422:Sequence Analysis, DNA; D012984:Software
D018076:DNA, Complementary; D012333:RNA, Messenger; D004247:DNA