Abstract
Abstract The recent literature on profile hidden Markov model (profile HMM) methods and software is reviewed. Profile HMMs turn a multiple sequence alignment into a position-specific scoring system suitable for searching databases for remotely homologous sequences. Profile HMM analyses complement standard pairwise comparison methods for large-scale sequence analysis. Several software implementations and two large libraries of profile HMMs of common protein domains are available. HMM methods performed comparably to threading methods in the CASP2 structure prediction exercise.
Keywords
Computer scienceMarkov modelMarkov chainHidden Markov modelArtificial intelligenceMachine learning
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Publication Info
- Year
- 1998
- Type
- review
- Volume
- 14
- Issue
- 9
- Pages
- 755-763
- Citations
- 5657
- Access
- Closed
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Cite This
Sean R. Eddy
(1998).
Profile hidden Markov models..
Bioinformatics
, 14
(9)
, 755-763.
https://doi.org/10.1093/bioinformatics/14.9.755
Identifiers
- DOI
- 10.1093/bioinformatics/14.9.755