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Hidden Markov models and optimized sequence alignments

✍ Scribed by L. Smith; L. Yeganova; W.J. Wilbur

Publisher
Elsevier Science
Year
2003
Tongue
English
Weight
179 KB
Volume
27
Category
Article
ISSN
1476-9271

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✦ Synopsis

We present a formulation of the Needleman-Wunsch type algorithm for sequence alignment in which the mutation matrix is allowed to vary under the control of a hidden Markov process. The fully trainable model is applied to two problems in bioinformatics: the recognition of related gene/protein names and the alignment and scoring of homologous proteins.

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