Title of article :
Efficient automatic exact motif discovery algorithms for biological sequences
Author/Authors :
Karci، نويسنده , , Ali، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2009
Abstract :
AbstractObjective
aper presents an algorithm for the solution of the motif discovery problem (MDP).
s and materials
discovery problem can be considered in two cases: motifs with insertions/deletions, and motifs without insertions/deletions. The first group motifs can be found by stochastic and approximated methods. The second group can be found by using stochastic and approximated methods, but also deterministic method. We proved that the second group motifs can be found with a deterministic algorithm, and so, it can be said that the second motifs finding is a P-type problem as proved in this paper.
s and conclusions
orithm was proposed in this paper for motif discovery problem. The proposed algorithm finds all motifs which are occurred in the sequence at least two times, and it also finds motifs of various sizes. Due to this case, this algorithm is regarded as Automatic Exact Motif Discovery Algorithm. All motifs of different sizes can be found with this algorithm, and this case was proven in this paper. It shown that automatic exact motif discovery is a P-type problem in this paper. The application of the proposed algorithm has been shown that this algorithm is superior to MEME, MEME3, Motif Sampler, WEEDER, CONSENSUS, AlignACE.
Keywords :
Motif Discovery , computational biology , DNA , Bioinformatics , Algorithms , Biological sequences
Journal title :
Expert Systems with Applications
Journal title :
Expert Systems with Applications