Microbial gene identification using interpolated Markov models.

S L Salzberg; A L Delcher; S Kasif; O White

doi:10.1093/nar/26.2.544

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Microbial gene identification using interpolated Markov models.

S L Salzberg·A L Delcher·S Kasif·O White

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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.

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Algorithms Base Sequence DNA, Bacterial Haemophilus influenzae Helicobacter pylori Markov Chains Open Reading Frames Sensitivity and Specificity Sequence Alignment Software Journal Article Research Support, U.S. Gov't, Non-P.H.S.Research Support, U.S. Gov't, P.H.S.

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S L Salzberg, A L Delcher, S Kasif, O White. 1998-01-15. Microbial gene identification using interpolated Markov models.. https://doi.org/10.1093/nar%2F26.2.544

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