Date of Award
2009
Publication Type
Master Thesis
Degree Name
M.Sc.
Department
Computer Science
Keywords
Artificial Intelligence.
Supervisor
Gras, Robin (Computer Science)
Rights
info:eu-repo/semantics/openAccess
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
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. We focuse 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, and consider integration of BOA and one simple heuristic. We also present application of our method in integration with decoding approach in a multiobjective optimization framework for solving the problem in case of multiple targets in the sample.
Recommended Citation
Soltan Ghoraie, Laleh, "Bayesian Optimization Algorithm for Non-unique Oligonucleotide Probe Selection" (2009). Electronic Theses and Dissertations. 337.
https://scholar.uwindsor.ca/etd/337