Please use this identifier to cite or link to this item:
https://scholarbank.nus.edu.sg/handle/10635/13516
DC Field | Value | |
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dc.title | Application of computational intelligence in biological sciences | |
dc.contributor.author | XU HUAN | |
dc.date.accessioned | 2010-04-08T10:33:48Z | |
dc.date.available | 2010-04-08T10:33:48Z | |
dc.date.issued | 2003-12-15 | |
dc.identifier.citation | XU HUAN (2003-12-15). Application of computational intelligence in biological sciences. ScholarBank@NUS Repository. | |
dc.identifier.uri | http://scholarbank.nus.edu.sg/handle/10635/13516 | |
dc.description.abstract | DNA 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.iso | en | |
dc.subject | DNA microarray, probe, evolutionary strategy, BLAST, premature convergence, Exon | |
dc.type | Thesis | |
dc.contributor.department | ELECTRICAL & COMPUTER ENGINEERING | |
dc.contributor.supervisor | TAY EE BENG, ARTHUR | |
dc.contributor.supervisor | NG HUCK HUI | |
dc.description.degree | Master's | |
dc.description.degreeconferred | MASTER OF ENGINEERING | |
dc.identifier.isiut | NOT_IN_WOS | |
Appears in Collections: | Master's Theses (Open) |
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xuhuan.pdf | 543.63 kB | Adobe PDF | OPEN | None | View/Download |
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