Hidden Markov Models of the G-Protein-Coupled Receptor Family
- 1 January 1994
- journal article
- research article
- Published by Mary Ann Liebert Inc in Journal of Computational Biology
- Vol. 1 (4), 311-336
- https://doi.org/10.1089/cmb.1994.1.311
Abstract
Hidden Markov Model techniques are used to derive a new model of the G-protein-coupled receptor family. The transition and emission parameters of the model are adjusted using a training set comprising 142 sequences. The resulting model is shown to perform well on a number of tasks, including multiple alignments, discrimination, large data base searches, classification, and fragment detection. General analytical results on the expectation and standard deviation of the likelihood of random sequences are also presented.Keywords
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