On the Monte-Carlo expectation maximization for finding motifs in DNA sequences.
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.
Aniruddha
A
Maiti
Anirban
A
Mukherjee
D000465:Algorithms; D004247:DNA / Q000032:analysis* / Q000737:chemistry*; D016208:Databases, Factual; D006801:Humans; D009010:Monte Carlo Method; D059372:Nucleotide Motifs / Q000235:genetics*; D016415:Sequence Alignment; D017422:Sequence Analysis, DNA / Q000379:methods*
D004247:DNA