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