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
Highly Influential
This paper has highly influenced 31 other papers. REVIEW HIGHLY INFLUENTIAL CITATIONS