Date of Award

2004

Publication Type

Master Thesis

Degree Name

M.Sc.

Department

Computer Science

Keywords

Computer Science.

Supervisor

Rueda, Luis,

Rights

info:eu-repo/semantics/openAccess

Abstract

Microarray (DNA chip) technology is having a significant impact on genomic studies. Many fields, including drug discovery and toxicological research, will certainly benefit from the use of DNA microarray technology. Microarray analysis is replacing traditional biological assays based on gels, filters and purification columns with small glass chips containing tens of thousands of DNA and protein sequences in agricultural and medical sciences. Microarray functions like biological microprocessors, enabling the rapid and quantitative analysis of gene expression patterns, patient genotypes, drug mechanisms and disease onset and progression on a genomic scale. Image analysis and statistical analysis are two important aspects of microarray technology. Gridding is necessary to accurately identify the location of each of the spots while extracting spot intensities from the microarray images and automating this procedure permits high-throughput analysis. Due to the deficiencies of the equipment that is used to print the arrays, rotations, misalignments, high contaminations with noise and artifacts, solving the grid segmentation problem in an automatic system is not trivial. The existing techniques to solve the automatic grid segmentation problem cover only limited aspect of this challenging problem and requires the user to specify or make assumptions about the spotsize, rows and columns in the grid and boundary conditions. An automatic gridding and spot quantification technique is proposed, which takes a matrix of pixels or a microarray image as input and makes no assumptions about the spotsize, rows and columns in the grid and is found to effective on datasets from GEO, Stanford genomic laboratories and on images obtained from private repositories. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2004 .V53. Source: Masters Abstracts International, Volume: 43-03, page: 0891. Adviser: Luis Rueda. Thesis (M.Sc.)--University of Windsor (Canada), 2004.

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