Function minimization in DNA sequence design based on binary particle swarm optimization

In DNA based computation and DNA nanotechnology, the design of good DNA sequences has turned out to be an elementary problem and one of the most practical and important research topics. Although the design of DNA sequences is dependent on the protocol of biological experiments, it is highly required...

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Bibliographic Details
Main Authors: Ibrahim, Zuwairie, Khalid, Noor Khafifah, Ibrahim, Ismail, Lim, Kian Sheng, Buyamin, Salinda, Md. Yusof, Zulkifli, Muhammad, Mohd. Saufee
Format: Article
Language:English
Published: Penerbit UTM Press 2011
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Online Access:http://eprints.utm.my/id/eprint/44937/1/ZuwairieIbrahim2011-FunctionMinimizationinDNASequenceDesign.pdf
http://eprints.utm.my/id/eprint/44937/
http://dx.doi.org/10.11113/jt.v54.819
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Summary:In DNA based computation and DNA nanotechnology, the design of good DNA sequences has turned out to be an elementary problem and one of the most practical and important research topics. Although the design of DNA sequences is dependent on the protocol of biological experiments, it is highly required to establish a method for the systematic design of DNA sequences, which could be applied to various design constraints. Basically, the fitness of DNA sequences can be evaluated using four objective functions, namely, similarity, Hmeasure, continuity and hairpin. In this paper, binary particle swarm optimization (BinPSO) is proposed to minimize those objective functions individually, subjected to two constraints: melting temperature and GCcontent. An implementation of the optimization process is presented using 20 particles and the results obtained shows the correctness of PSO computation, where the minimized values for each objective can be achieved.