摘要: Hidden Markov Model techniques are used to derive a new model of the G-protein-coupled receptor family. The transition and emission parameters adjusted using training set comprising 142 sequences. resulting is shown perform well on number tasks, including multiple alignments, discrimination, large data base searches, classification, fragment detection. General analytical results expectation standard deviation likelihood random sequences also presented.
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