review Open AccessTop 1% cited
Profile hidden Markov models.
Bioinformatics · 1998 · Vol. 14(9) · pp. 755–763
Sean R. Eddy✉(Washington University in St. Louis)
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.
Algorithms and Data CompressionNatural Language Processing TechniquesSpeech Recognition and SynthesisComputer scienceMarkov modelMarkov chainHidden Markov modelArtificial intelligenceMachine learning
MeSH terms
HumansMarkov ChainsSoftwareSequence AlignmentPeptide Library
Funding
- University of California, Santa Cruz
- National Institutes of Health
- National Human Genome Research Institute
Citations
5,777
FWCI
61.47
field-weighted impact
References
68
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100%
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