Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 16 of 16 for “"Microarray Data Analysis"”.
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Bioinformatics framework for genotyping microarray data analysis
… in high-throughput instrumentation and microarray data analysis. Genotyping microarrays establish the genotypes of DNA sequences containing single nucleotide polymorphisms (SNPs), and can help biologists probe the functions of different genes and/or construct complex gene interaction …
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DNA Microarray Data Analysis and Mining: Affymetrix Software Package and In-House Complementary Packages
Data management and analysis represent a major challenge for microarray studies. In this study, Affymetrix software was used to analyze an HIV-infection data. The microarray analysis shows remarkably different results when using different parameters provided by the software. This highlights the …
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Microarray data analysis methods and their applications to gene expression data analysis for Saccharomyces cerevisiae under oxidative stress
… at 3 minute after the exposure. Statistical analysis methods, including ANOVA, k-means clustering analysis, and pathway analysis were used to analyze the data. The results from this study provide a dynamic resolution of the oxidative stress responses in S. cerevisiae, and contribute to a …
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Real-time Three-Dimensional DNA Microarrays: How Well Can We Distinguish Between Related Target Sequences?
DNA microarrays, due to their highly parallel nature, are in principle well suited for rapid identification of known or related microbial species, but our ability to extract meaningful information from microarray images is still at a rudimentary level. The use of DNA microarrays is currently …
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Non-parametric algorithms for evaluating gene expression in cancer using DNA microarray technology
Microarray technology has transformed the field of cancer biology by enabling the simultaneous evaluation of tens of thousands mRNA expression levels in a single experiment. This technology has been applied to medical science in order to find gene expression markers that cluster diseased and normal …
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Fusion: a Visualization Framework for Interactive Ilp Rule Mining With Applications to Bioinformatics
Microarrays provide biologists an opportunity to find the expression profiles of thousands of genes simultaneously. Biologists try to understand the mechanisms underlying the life processes by finding out relationships between gene-expression and their functional categories. Fusion is a software …
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An improved microarray image analysis architecture using mathematical morphology
DNA microarrays are now widely used to measure gene expression levels of healthy and cancerous cells. To allow further experiment for drug development to treat cancer, colour intensity from images of microarray spots need to be extracted as accurate as possible. The intensity extraction requires …
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Bioinformatics study of mammalian MRNA polydenylation
… genomes, together with their gene expression data provides valuable resources to study mRNA polyadenylation on a system level. This dissertation addresses the following issues of mammalian mRNA polyadenylation through bioinformatics approaches: (1) the extensive documentation of several key …
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The control of the false discovery rate under structured hypotheses
… such as Gene Ontology in gene expression data. However, few false discovery rate (FDR) controlling procedures take advantage of this inherent structure. In this dissertation, we develop FDR controlling methods which exploit the structural information of the hypotheses. First, we study the …
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Genetic, Genomic, and Breeding Approaches to Further Explore Kernel Composition Traits and Grain Yield in Maize
… of distributions for starch were selected and a microarray platform was used to assess gene expression profile differential in developing kernels of selected materials sampled at 15 and 20 days after pollination. Microarray data analysis revealed a repertoire of differentially expressed genes …
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Survival Prediction For Brain Tumor Patients Using Gene Expression Data
… profiles (U133 Affymetrix gene expression microarrays) along with clinical information. First, a predictive Random Forest model is built for binary outcomes (i.e. short vs. long-term survival) and a small subset of genes whose expression values can be used to predict survival time is …
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EMMA2 : a MAGE-compliant system for the analysis of microarray data in integrated functional genomics
… to study gene-expression and metabolic pathways. Microarrays have become a highly popular method to measure the transcriptional regulation in functional genomics. Microarrays allow to measure the expression levels of thousands of genes in parallel, but the measured datasets contain a certain level …
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Statistical Methods for Genetic Pathway-Based Data Analysis
The wide application of the genomic microarray technology triggers a tremendous need in the development of the high dimensional genetic data analysis. Many statistical methods for the microarray data analysis consider one gene at a time, but they may miss subtle changes at the single gene level. …
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Novel Monte Carlo Approaches to Identify Aberrant Pathways in Cancer
… have promoted the integration of multi-platform data to investigate signal transduction pathways within a cell. In order to model complicated dynamics and heterogeneity of biological pathways, sophisticated computational models are needed to address unique properties of both the biological …
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Integrative Modeling and Analysis of High-throughput Biological Data
… models and algorithms to interpret biological data so as to understand biological problems. With current high-throughput technology development, different types of biological data can be measured in a large scale, which calls for more sophisticated computational methods to analyze and interpret …
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Multiple testing in spatial epidemiology: a Bayesian approach
… the preliminary study perspective that an analysis on SMR indicators is asked to. We implement the control of the FDR, a quantity largely used to address multiple comparisons problems in the eld of microarray data analysis but which is not usually employed in disease mapping. Controlling …