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• W203965441 abstract "One important application of DNA microarrays is measuring the expression levels of genes. The quality of the microarrays design which includes selecting short Oligonucleotide sequences (probes) to be affixed on the surface of the microarray becomes a major issue. A good design is the one that contains the minimum possible number of probes while having an acceptable ability in identifying the targets existing in the sample. This thesis focuses on the problem of computing the minimal set of probes which is able to identify each target of a sample, referred to as Non-unique Oligonucleotide Probe Selection. We present the application of an Estimation of Distribution Algorithm named Bayesian Optimization Algorithm (BOA) to this problem. This approach considers integration of BOA and one simple heuristic. The obtained results compare favorably with the state-of-the-art methods. We also present application of our method in integration with decoding approach in a multiobjective optimization framework for solving the problem in the case of multiple targets in the sample." @default.
• W203965441 created "2016-06-24" @default.
• W203965441 creator A5012749927 @default.
• W203965441 date "2009-01-01" @default.
• W203965441 modified "2023-09-27" @default.
• W203965441 title "Bayesian Optimization Algorithm for Non-unique Oligonucleotide Probe Selection" @default.
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• W203965441 hasPublicationYear "2009" @default.
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