Microbial gene identification using interpolated Markov models.
This paper describes a new system, GLIMMER, for finding genes in microbial genomes. In a series of tests on Haemophilus influenzae , Helicobacter pylori and other complete microbial genomes, this system has proven to be very accurate at locating virtually all the genes in these sequences, outperforming previous methods. A conservative estimate based on experiments on H.pylori and H. influenzae is that the system finds >97% of all genes. GLIMMER uses interpolated Markov models (IMMs) as a framework for capturing dependencies between nearby nucleotides in a DNA sequence. An IMM-based method makes predictions based on a variable context; i.e., a variable-length oligomer in a DNA sequence. The context used by GLIMMER changes depending on the local composition of the sequence. As a result, GLIMMER is more flexible and more powerful than fixed-order Markov methods, which have previously been the primary content-based technique for finding genes in microbial DNA.
Salzberg
S L
SL
The Institute for Genomic Research, 9712 Medical Center Drive, Rockville, MD 20850, USA. salzberg@tigr.org
Delcher
A L
AL
Kasif
S
S
White
O
O
D000465:Algorithms; D001483:Base Sequence; D004269:DNA, Bacterial / Q000032:analysis* / Q000737:chemistry; D006193:Haemophilus influenzae / Q000235:genetics; D016480:Helicobacter pylori / Q000235:genetics; D008390:Markov Chains; D016366:Open Reading Frames; D012680:Sensitivity and Specificity; D016415:Sequence Alignment; D012984:Software
D004269:DNA, Bacterial