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Hidden Markov models and optimized sequence alignments
L Smith1, L Yeganova, W J Wilbur
1Computational Biology Branch, National Center for Biotechnology Information, National Library of Medicine, Rm. 614D, Bldg. 38A, 8600 Rockville Pike, Bethesda, MD 20894, USA. lsmith@ncbi.nlm.nih.gov
Computational Biology and Chemistry
|June 12, 2003
Abstract:
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.