Microbial gene identification using interpolated Markov models

Nucleic Acids Res. 1998 Jan 15;26(2):544-8. doi: 10.1093/nar/26.2.544.


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.

Publication types

  • Research Support, U.S. Gov't, Non-P.H.S.
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Algorithms
  • Base Sequence
  • DNA, Bacterial / analysis*
  • DNA, Bacterial / chemistry
  • Haemophilus influenzae / genetics
  • Helicobacter pylori / genetics
  • Markov Chains*
  • Open Reading Frames
  • Sensitivity and Specificity
  • Sequence Alignment
  • Software


  • DNA, Bacterial