“School of Biological”

Back to Papers Home
Back to Papers of School of Biological

Paper   IPM / Biological / 13213
School of Biological Sciences
  Title:   A Bidirectional Hidden Markov Model In Linear Memory
  Author(s): 
1.  N. Ejlali.
2.  H. Pezeshk.
  Status:   Published
  Journal: Journal of Statistical Science
  No.:  2
  Vol.:  2
  Year:  2010
  Pages:   131-148
  Supported by:  IPM
  Abstract:
Hidden Markov models are widely used in Bioinformatics. They are applied to protein sequence alignment, protein family annotation and gene-finding.The Baum-Welch training is an expectation-maximization algorithm for training the emission and transition probabilities of hidden Markov models. For very long training sequence, even the most efficient algorithms are memory-consuming. In this paper we discuss different approaches to decrease the memory use and compare the performance of different algorithms. In addition, we propose a bidirection algorithm with linear memory. We apply this algorithm to simulated data of protein profile to analyze the strength and weakness of the algorithm.

Download TeX format
back to top
scroll left or right