Multiple Alignment Using Hidden Markov Models

  title={Multiple Alignment Using Hidden Markov Models},
  author={Sean R. Eddy},
  journal={Proceedings. International Conference on Intelligent Systems for Molecular Biology},
A simulated annealing method is described for training hidden Markov models and producing multiple sequence alignments from initially unaligned protein or DNA sequences. Simulated annealing in turn uses a dynamic programming algorithm for correctly sampling suboptimal multiple alignments according to their probability and a Boltzmann temperature factor. The quality of simulated annealing alignments is evaluated on structural alignments of ten different protein families, and compared to the… CONTINUE READING
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