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Microbial gene identification using interpolated Markov models (1998)
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| Venue: | Nucleic Acids Research |
| Citations: | 252 - 11 self |
BibTeX
@ARTICLE{Salzberg98microbialgene,
author = {Steven L. Salzberg and Arthur L. Delcher and Simon Kasif and Owen White},
title = {Microbial gene identification using interpolated Markov models},
journal = {Nucleic Acids Research},
year = {1998},
volume = {26},
pages = {544--548}
}
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Abstract
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.
Keyphrases
interpolated markov model microbial gene identification dna sequence helicobacter pylorus haemophilus influenzae local composition variable-length oligomer nearby nucleotide glimmer change microbial genome variable context conservative estimate imm-based method primary content-based technique microbial dna markov model complete microbial genome new system previous method fixed-order markov method
