Microarray technology like that of recombinant DNA and the polymerase chain reaction is a foundational component of modern biotechnology. There are many aspects in the manufacture of a DNA chip and each serves as a contributing variable to the overall performance of the device. Commercial production of microarrays commenced before a basic understanding of the physical and chemical processes that govern the many variables was attained and the role of each on the performance of microarrays was understood. The consequence of this has been non-optimal performance of this technology and variable results from microarray analyses. Recent studies have shown that part of the variability in the use of commercially available microarrays relates to insufficient control of the surface chemistry within a microarray spot and between spots. Although the ideal characteristics of a microarray surface have been identified, existing surfaces and the ongoing proliferation of alternative ones do not address these sufficiently in order to reduce the sources of error arising from the surface of a microarray. Hence, the application of physico-chemical techniques in the development of microarrays surfaces can assist in improving the performance of these devices. / Thesis (PhDApSc(MineralsandMaterials))--University of South Australia, 2006.

The aim of this research was to assemble sufficient experimental evidence about candidate gene transcript expression changes between non-neoplastic and neo- plastic colorectal tissues to justify future assay development involving promis- ing leads. To achieve this aim, this thesis explores the hypothesis that gene expression-based biomarkers can be used to accurately discriminate colorectal neoplastic tissues from non-neoplastic controls. This hypothesis was tested by first analysing multiple, large, quality controlled data sets comprising gene expression measurements across colorectal phenotypes to discover potential biomarkers. Candidate biomarkers were then subjected to validation testing using a custom-design oligonucleotide microarray applied to independently derived clinical specimens. A number of novel conclusions are reached based on these data. The most important conclusion is that a defined subset of genes expressed in the colorectal mucosa are reliably differentially ex- pressed in neoplastic tissues. In particular, the apparently high prediction accu- racy achieved for single gene transcripts to discriminate hundreds of neoplastic and non-neoplastic tissues provides compelling evidence that the resulting can- didate genes are worthy of further biomarker research. In addition to addressing the central hypothesis, additional contributions are made to the field of colorectal neoplasia gene expression profiling. These contributions include: The first systematic analysis of gene expression in non-diseased tissues along the colorectum To better understand the range of gene expression in non-diseased tissues, RNA extracts taken from along the longitudinal axis of the large intestine were studied. The development of quality control methodologies for high dimen- sional gene expression data Complex data collection platforms such as oligonucleotide microarrays introduce the potential for unrecognized confound- ing variables. The exploration of quality control parameters across five hundred microarray experiments provided insights about quality control techniques. The design of a custom microrray comprised of oligonucleotide probe- sets hybridising to RNA transcripts differentially expressed in neo- plastic colorectal specimens A custom design oligonucleotide microarray was designed and tested combining the results of multiple biomarker discovery projects. Introduction of a method to filter differentially expressed genes dur- ing discovery that may improve validation efficiencies of biomarker discovery based on gene expression measurements Differential expression discovery research is typically focused only on quantitative changes in transcript concentration between phenotype contrasts. This work introduces a method for generating hypotheses related to transcripts which may be quali- tatively “switched-on” between phenotypes. Identification of mRNA transcripts which are differentially expressed between colorectal adenomas and colorectal cancer tissues Transcripts differentially expressed between adenomatous and cancerous RNA extracts were discovered and then tested in independent tissues. In conclusion, these results confirm the hypothesis that gene expression profiling can discriminate colorectal neoplasia (including adenomas) from non-neoplastic controls. These results also establish a foundation for an ongoing biomarker development program.

Consistency modeling for gene selection is a new topic emerging from recent cancer bioinformatics research. The result of classification or clustering on a training set was often found very different from the same operations on a testing set. Here, the issue is addressed as a consistency problem. In practice, the inconsistency of microarray datasets prevents many typical gene selection methods working properly for cancer diagnosis and prognosis. In an attempt to deal with this problem, a new concept of performance-based consistency is proposed in this thesis.An interesting finding in our previous experiments is that by using a proper set of informative genes, we significantly improved the consistency characteristic of microarray data. Therefore, how to select genes in terms of consistency modelling becomes an interesting topic. Many previously published gene selection methods perform well in the cancer diagnosis domain, but questions are raised because of the irreproducibility of experimental results. Motivated by this, two new gene selection methods based on the proposed performance-based consistency concept, GAGSc (Genetic Algorithm Gene Selection method in terms of consistency) and LOOLSc (Leave-one-out Least-Square bound method with consistency measurement) were developed in this study with the purpose of identifying a set of informative genes for achieving replicable results of microarray data analysis.The proposed consistency concept was investigated on eight benchmark microarray and proteomic datasets. The experimental results show that the different microarray datasets have different consistency characteristics, and that better consistency can lead to an unbiased and reproducible outcome with good disease prediction accuracy.As an implementation of the proposed performance-based consistency, GAGSc and LOOLSc are capable of providing a small set of informative genes. Comparing with those traditional gene selection methods without using consistency measurement, GAGSc and LOOLSc can provide more accurate classification results. More importantly, GAGSc and LOOLSc have demonstrated that gene selection, with the proposed consistency measurement, is able to enhance the reproducibility in microarray diagnosis experiments.

Thesis (Ph.D.)--Tufts University, 2004. / Adviser: David R. Walt. Submitted to the Dept. of Chemistry. Includes bibliographical references. Access restricted to members of the Tufts University community. Also available via the World Wide Web;

Thesis (Ph. D.)--University of Texas at Austin, 2007. / Vita. Includes bibliographical references.

Thesis (Ph. D.)--University of Texas at Austin, 2007. / Vita. Includes bibliographical references.

Diss. (sammanfattning) Uppsala : Univ., 2005. / Härtill 4 uppsatser.

Thesis (Ph. D.)--University of Texas at Austin, 2008. / Vita. Includes bibliographical references.

Thesis (MSc Natural and Agricultural Sciences (Genetics))--University of Pretoria, 2007. / Includes summary. Includes bibliographical references. Available on the Internet via the World Wide Web.

Thesis (M.S.)--University of Missouri-Columbia, 2007. / The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file (viewed on April 9, 2009) Vita. Includes bibliographical references.