Genetic algorithm for dyad pattern finding in DNA sequences
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概要
- 論文の詳細を見る
In this paper a novel genetic algorithm is presented for the dyad motif finding problem. The genetic algorithm uses a multi-objective fitness function based on the sum of pairs, the number of matches, and the information content. The individuals required for the population pool in the genetic algorithm are optimized by Gibbs sampling method. Also, new crossover and mutation operators are designed. The algorithm is implemented and tested on the different types of real datasets. The results are compared with other well-known algorithms and the effectiveness of our algorithm is shown.
- 日本遺伝学会の論文
- 2009-02-25
著者
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Goliaei Bahram
Department Of Bioinformatics Institute Of Biochemistry And Biophysics University Of Tehran
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ZARE-MIRAKABAD Fatemeh
Department of Bioinformatics, Institute of Biochemistry and Biophysics, University of Tehran
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AHRABIAN Hayedeh
Department of Bioinformatics, Institute of Biochemistry and Biophysics, University of Tehran
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SADEGHI Mehdi
National Institute of Genetic Engendering and Biotechnology
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HASHEMIFAR Somaieh
Center of Excellence in Biomathematics, School of Mathematics, Statistics, and Computer Science, Uni
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NOWZARI-DALINI Abbas
Department of Bioinformatics, Institute of Biochemistry and Biophysics, University of Tehran
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Ahrabian Hayedeh
Department Of Bioinformatics Institute Of Biochemistry And Biophysics University Of Tehran
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Hashemifar Somaieh
Center Of Excellence In Biomathematics School Of Mathematics Statistics And Computer Science Univers
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Nowzari-dalini Abbas
Department Of Bioinformatics Institute Of Biochemistry And Biophysics University Of Tehran
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Zare-mirakabad Fatemeh
Department Of Bioinformatics Institute Of Biochemistry And Biophysics University Of Tehran