Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/13516
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dc.titleApplication of computational intelligence in biological sciences
dc.contributor.authorXU HUAN
dc.date.accessioned2010-04-08T10:33:48Z
dc.date.available2010-04-08T10:33:48Z
dc.date.issued2003-12-15
dc.identifier.citationXU HUAN (2003-12-15). Application of computational intelligence in biological sciences. ScholarBank@NUS Repository.
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/13516
dc.description.abstractDNA microarray is an important tools in genome research. To conduct a DNA microarray test, a set of pre-defined probe is essential. A qualified probe should satisfy three criteria, namely, uniqueness criteria, melting-temperature criteria and no self-folding criteria. Traditional method regarding probe searching is the enumeration method, which is computational expernsive. We used evuotionary strategy in searching probes of yeast DNA microarray and human DNA microarray. In searching yeast probe, the classic evolutionary stratey is modified so that fewer tests were performed on the uniqueness criteria, which need more time than other two criteria. Also, adjustments are made to solve premature convergence. In searching human probe, Basic Local Alignment Search Tools (BLAST) are used so that the time on uniqueness criteria test is substantially decreased. The result is compared with enumeration method to demonstrate the effectiveness of evolutionary strategy in probe searching problem.
dc.language.isoen
dc.subjectDNA microarray, probe, evolutionary strategy, BLAST, premature convergence, Exon
dc.typeThesis
dc.contributor.departmentELECTRICAL & COMPUTER ENGINEERING
dc.contributor.supervisorTAY EE BENG, ARTHUR
dc.contributor.supervisorNG HUCK HUI
dc.description.degreeMaster's
dc.description.degreeconferredMASTER OF ENGINEERING
dc.identifier.isiutNOT_IN_WOS
Appears in Collections:Master's Theses (Open)

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