Hidden Markov models in computational biology. Applications to protein modeling.

@article{Krogh1993HiddenMM,
  title={Hidden Markov models in computational biology. Applications to protein modeling.},
  author={Anders Krogh and Mg Brown and I. Saira Mian and Kimmen Sj{\"o}lander and David Haussler},
  journal={Journal of molecular biology},
  year={1993},
  volume={235 5},
  pages={
          1501-31
        }
}
  • Anders Krogh, Mg Brown, +2 authors David Haussler
  • Published in Journal of molecular biology 1993
  • Biology, Medicine
  • Hidden Markov Models (HMMs) are applied to the problems of statistical modeling, database searching and multiple sequence alignment of protein families and protein domains. These methods are demonstrated on the globin family, the protein kinase catalytic domain, and the EF-hand calcium binding motif. In each case the parameters of an HMM are estimated from a training set of unaligned sequences. After the HMM is built, it is used to obtain a multiple alignment of all the training sequences. It… CONTINUE READING

    Create an AI-powered research feed to stay up to date with new papers like this posted to ArXiv

    Citations

    Publications citing this paper.
    SHOWING 1-10 OF 1,135 CITATIONS, ESTIMATED 98% COVERAGE

    Machine learning can differentiate venom toxins from other proteins having non-toxic physiological functions

    VIEW 7 EXCERPTS
    CITES METHODS & BACKGROUND
    HIGHLY INFLUENCED

    The identification and characterisation of microbes in complex environments

    VIEW 6 EXCERPTS
    CITES BACKGROUND & METHODS
    HIGHLY INFLUENCED

    Exploring the function and evolution of proteins using domain families

    VIEW 15 EXCERPTS
    CITES BACKGROUND
    HIGHLY INFLUENCED

    Recherche de nouvelles hormones peptidiques codées par le génome humain

    VIEW 17 EXCERPTS
    CITES METHODS & BACKGROUND
    HIGHLY INFLUENCED

    Searching for novel peptide hormones in the human genome

    VIEW 17 EXCERPTS
    CITES METHODS & BACKGROUND
    HIGHLY INFLUENCED

    Specialized Hidden Markov Model Databases for Microbial Genomics

    • Martin Gollery
    • Biology, Medicine
    • Comparative and functional genomics
    • 2003
    VIEW 5 EXCERPTS
    CITES BACKGROUND
    HIGHLY INFLUENCED

    Variations on probabilistic suffix trees: statistical modeling and prediction of protein families

    VIEW 16 EXCERPTS
    CITES BACKGROUND
    HIGHLY INFLUENCED

    FILTER CITATIONS BY YEAR

    1993
    2020

    CITATION STATISTICS

    • 89 Highly Influenced Citations

    • Averaged 29 Citations per year from 2017 through 2019

    References

    Publications referenced by this paper.
    SHOWING 1-10 OF 39 REFERENCES

    Protein kinase classification.

    VIEW 10 EXCERPTS
    HIGHLY INFLUENTIAL

    Protein alignment and clustering

    • 1992
    VIEW 3 EXCERPTS
    HIGHLY INFLUENTIAL

    Reconstruction and analysis of human alu genes

    Profile analysis.

    HMM with protein structure grammar

    Hidden Markov models and iterative aligners

    • J. Mol. Biol. Tanaka, M. H. Ishikawa, K. Asai, A. Konagaya
    • 1993

    Protein modeling

    • K. Sjiilander
    • 1993
    VIEW 1 EXCERPT

    Protein modeling using hidden Markov models: analysis of globins

    Structural analysis based on state-space modeling.