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Markov models — training and evaluation of hidden Markov models

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“With one eye you are looking at the outside world, while with the other you are looking within yourself.” —Amedeo Modigliani

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Fig. 1: Modeling and parameter estimation of a Hidden Markov model (HMM) for an unstable coin.
Fig. 2: The calculation of the forward and backward probabilities for the training sequence HHTTT using initial estimates.
Fig. 3: Accuracy of HMM parameter estimates improves with larger training sets.

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Authors and Affiliations

  1. Canada’s Michael Smith Genome Sciences Centre, Vancouver, British Columbia, Canada

    Jasleen K. Grewal & Martin Krzywinski

  2. Department of Statistics, The Pennsylvania State University, State College, PA, USA

    Naomi Altman

Authors
  1. Jasleen K. Grewal
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  2. Martin Krzywinski
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  3. Naomi Altman
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Correspondence to Martin Krzywinski.

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Grewal, J.K., Krzywinski, M. & Altman, N. Markov models — training and evaluation of hidden Markov models. Nat Methods 17, 121–122 (2020). https://doi.org/10.1038/s41592-019-0702-6

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