A novel approach of finding planted motif in biological sequences

Nazmul, Rumana; Chowdhury, Ahsan Raja; Tareeq, Saifuddin Md.

doi:10.1109/iccitechn.2007.4579353

Cited by 1 publication

(1 citation statement)

References 10 publications

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“…The second group contains all methods that find an approximate solution. The methods in this group are based on different strategies such as probabilistic, greedy, and soft computing such as genetic, ant colony and swarm (Nazmul et al, 2007;Chengwei and Jianhua, 2009;Li and Wang, 2010;Li and Wang, 2009;Chan et al, 2008;Clerc and Kennedy, 2002;Li and Tompa, 2006;Sze and Zhao, 2006). All these techniques depend on finding local optimal solution.…”

Section: Introductionmentioning

confidence: 99%

Identification of DNA motif using particle swarm optimization technique

Khedr

2017

Int. j. adv. appl. sci

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The process of discovering short recurring patterns in DNA called DNA motif. DNA motif is an important part to study the biological cell functions. The main challenging of DNA motif is the running time to identify the motif where it increases with the length of motif and the number of mutations. Particle swarm optimization (PSO) is one of the efficient techniques to find an approximate solution using global optimization technique. We propose a PSO algorithm to find DNA motif. The experimental study on artificial data shows that the running time of the proposed algorithm is faster than recent proposed algorithms. The proposed algorithm is also compared to voting and hybrid algorithms for performance measure. In addition, the accuracy of the proposed algorithm is 90%. Finally, we apply the proposed algorithm on real data includes PDR3, GAL4, MATalpha2, and MCB.

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Section: Introductionmentioning

confidence: 99%

Identification of DNA motif using particle swarm optimization technique

Khedr

2017

Int. j. adv. appl. sci

View full text Add to dashboard Cite

show abstract

A novel approach of finding planted motif in biological sequences

Cited by 1 publication

References 10 publications

Identification of DNA motif using particle swarm optimization technique

Identification of DNA motif using particle swarm optimization technique

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