Efficient algorithms for training the parameters of hidden Markov models using stochastic expectation maximization (EM) training and Viterbi training
<p>Abstract</p> <p>Background</p> <p>Hidden Markov models are widely employed by numerous bioinformatics programs used today. Applications range widely from comparative gene prediction to time-series analyses of micro-array data. The parameters of the underlying models...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2010-12-01
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| Series: | Algorithms for Molecular Biology |
| Online Access: | http://www.almob.org/content/5/1/38 |