DocumentCode :
109983
Title :
On the Monte-Carlo Expectation Maximization for Finding Motifs in DNA Sequences
Author :
Maiti, Aniruddha ; Mukherjee, Anirban
Author_Institution :
Dept. of Electr. Eng., Indian Inst. of Technol. Kharagpur, Kharagpur, India
Volume :
19
Issue :
2
fYear :
2015
fDate :
Mar-15
Firstpage :
677
Lastpage :
686
Abstract :
Finding conserved locations or motifs in genomic sequences is of paramount importance. Expectation maximization (EM)-based algorithms are widely employed to solve motif finding problems. The present study proposes a novel initialization technique and model-shifting scheme for Monte-Carlo-based EM methods for motif finding. Two popular EM-based motif finding algorithms are compared to the proposed method, which offers improved motif prediction accuracy on a synthetic dataset and a true biological dataset.
Keywords :
DNA; Monte Carlo methods; biology computing; expectation-maximisation algorithm; genomics; molecular biophysics; molecular configurations; DNA sequences; EM-based motif finding algorithms; Monte-Carlo expectation maximization-based algorithms; biological dataset; genomic sequences; initialization technique; model-shifting scheme; motif finding problems; motif prediction accuracy; synthetic dataset; Biological system modeling; Biomedical measurement; Clustering algorithms; Computational modeling; Markov processes; Monte Carlo methods; Silicon; DNA; Monte-Carlo; expectation maximization (EM); motif finding;
fLanguage :
English
Journal_Title :
Biomedical and Health Informatics, IEEE Journal of
Publisher :
ieee
ISSN :
2168-2194
Type :
jour
DOI :
10.1109/JBHI.2014.2322694
Filename :
6812135
Link To Document :
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