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Dissertations / Theses on the topic 'Microarray'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Pernagallo, Salvatore. "Biocompatible polymer microarrays for cellular high-content screening." Thesis, University of Edinburgh, 2010. http://hdl.handle.net/1842/7571.

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The global aim of this thesis was to study the use of microarray technology for the screening and identification of biocompatible polymers, to understand physiological phenomena, and the design of biomaterials, implant surfaces and tissue-engineering scaffolds. This work was based upon the polymer microarray platform developed by the Bradley group. Polymer microarrays were successfully applied to find the best polymer supports for: (i) mouse fibroblast cells and used to evaluate cell biocompatibility and cell morphology. Fourteen polyurethanes demonstrated significant cellular adhesion. (ii) A

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2

Wang, Tao. "Statistical design and analysis of microarray experiments." Connect to this title online, 2005. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1117201363.

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Thesis (Ph. D.)--Ohio State University, 2005.<br>Title from first page of PDF file. Document formatted into pages; contains ix, 146 p.; also includes graphics (some col.) Includes bibliographical references (p. 145-146). Available online via OhioLINK's ETD Center

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3

Klenkar, Goran. "Protein Microarray Chips." Doctoral thesis, Linköping : Univ, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-8904.

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4

Harness, Denise. "A Comparison of Unsupervised Methods for DNA Microarray Leukemia Data." Digital Commons @ East Tennessee State University, 2018. https://dc.etsu.edu/asrf/2018/schedule/106.

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Advancements in DNA microarray data sequencing have created the need for sophisticated machine learning algorithms and feature selection methods. Probabilistic graphical models, in particular, have been used to identify whether microarrays or genes cluster together in groups of individuals having a similar diagnosis. These clusters of genes are informative, but can be misleading when every gene is used in the calculation. First feature reduction techniques are explored, however the size and nature of the data prevents traditional techniques from working efficiently. Our method is to use the pa

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5

Dvergsten, Erik C. "A Weighted Gene Co-expression Network Analysis for Streptococcus sanguinis Microarray Experiments." VCU Scholars Compass, 2016. http://scholarscompass.vcu.edu/etd/4430.

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Streptococcus sanguinis is a gram-positive, non-motile bacterium native to human mouths. It is the primary cause of endocarditis and is also responsible for tooth decay. Two-component systems (TCSs) are commonly found in bacteria. In response to environmental signals, TCSs may regulate the expression of virulence factor genes. Gene co-expression networks are exploratory tools used to analyze system-level gene functionality. A gene co-expression network consists of gene expression profiles represented as nodes and gene connections, which occur if two genes are significantly co-expressed. An adj

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6

Hernández-Cabronero, Miguel. "DNA Microarray Image Compression." Doctoral thesis, Universitat Autònoma de Barcelona, 2015. http://hdl.handle.net/10803/297706.

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En los experimentos con DNA microarrays se genran dos imágenes monocromo, las cuales es conveniente almacenar para poder realizar análisis más precisos en un futuro. Por tanto, la compresión de imágenes surge como una herramienta particularmente útil para minimizar los costes asociados al almacenamiento y la transmisión de dichas imágenes. Esta tesis tiene por objetivo mejorar el estado del arte en la compresión de imágenes de DNA microarrays. Como parte de esta tesis, se ha realizado una detallada investigación de las características de las imágenes de DNA microarray. Los resultados experi

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7

Downes, Aidan Rawle. "Microarray submissions to Experibase." Thesis, Massachusetts Institute of Technology, 2005. http://hdl.handle.net/1721.1/33281.

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Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2005.<br>Includes bibliographical references (leaf 32, first group).<br>Experibase is an experimental database that supports the storage of data from leading biological experiment techniques. Experibase ontology was extended to include a robust representation of microarray data, a leading experimental technique. The microarray submission system takes advantage of Experibase's new microarray storage capabilities by allowing biologist to submit microarray data to Experibase using an app

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8

Mao, Shihong. "Comparative Microarray Data Mining." Wright State University / OhioLINK, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=wright1198695415.

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9

Stephens, Nathan Wallace. "A Comparison of Microarray Analyses: A Mixed Models Approach Versus the Significance Analysis of Microarrays." BYU ScholarsArchive, 2006. https://scholarsarchive.byu.edu/etd/1115.

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DNA microarrays are a relatively new technology for assessing the expression levels of thousands of genes simultaneously. Researchers hope to find genes that are differentially expressed by hybridizing cDNA from known treatment sources with various genes spotted on the microarrays. The large number of tests involved in analyzing microarrays has raised new questions in multiple testing. Several approaches for identifying differentially expressed genes have been proposed. This paper considers two: (1) a mixed models approach, and (2) the Signiffcance Analysis of Microarrays.

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10

Fronczyk, Kassandra M. "Development of Informative Priors in Microarray Studies." Diss., CLICK HERE for online access, 2007. http://contentdm.lib.byu.edu/ETD/image/etd2031.pdf.

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11

Nowacki, Sandra. "DPC4-Zielgenidentifikation mittels Microarray-Technologie." [S.l.] : [s.n.], 2005. http://deposit.ddb.de/cgi-bin/dokserv?idn=975910027.

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12

Lau, Kelvin Ee Ming. "Microarray analysis of Acidovorax temperans." Thesis, University of Auckland, 2008. http://hdl.handle.net/2292/5869.

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Bacteria belonging to the genus Acidovorax have been shown to be a consistent member of the activated sludge microbial community. Two phenotypic variants of A. temperans CB2 isolated locally from activated sludge exhibit noteworthy characteristics, such as the ability to form biofilms and flocs, which are critical microbial processes underlying all modern wastewater treatment systems. Gene expression microarray technology is a functional genomics platform that enables the simultaneous interrogation of all expressed transcripts during normal cell ontogeny, or in response to specific envir

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13

O'Neill, Paul. "Improved analysis of microarray images." Thesis, Brunel University, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.435755.

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14

Selvaraja, Sudarshan. "Microarray Data Analysis Tool (MAT)." University of Akron / OhioLINK, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=akron1227467806.

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15

Stephens, Nathan W. "A comparison of genetic microarray analyses : a mixed models approach versus the significance analysis of microarrays /." Diss., CLICK HERE for online access, 2006. http://contentdm.lib.byu.edu/ETD/image/etd1604.pdf.

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16

Zhou, Feng. "Contaminated Chi-square Modeling and Its Application in Microarray Data Analysis." UKnowledge, 2014. http://uknowledge.uky.edu/statistics_etds/7.

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Mixture modeling has numerous applications. One particular interest is microarray data analysis. My dissertation research is focused on the Contaminated Chi-Square (CCS) Modeling and its application in microarray. A moment-based method and two likelihood-based methods including Modified Likelihood Ratio Test (MLRT) and Expectation-Maximization (EM) Test are developed for testing the omnibus null hypothesis of no contamination of a central chi-square distribution by a non-central Chi-Square distribution. When the omnibus null hypothesis is rejected, we further developed the moment-based test an

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17

Fujita, André. "Análise de dados de expressão gênica: normalização de microarrays e modelagem de redes regulatórias." Universidade de São Paulo, 2007. http://www.teses.usp.br/teses/disponiveis/95/95131/tde-14092007-173758/.

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A análise da expressão gênica através de dados gerados em experimentos de microarrays de DNA vem possibilitando uma melhor compreensão da dinâmica e dos mecanismos envolvidos nos processos celulares ao nível molecular. O aprimoramento desta análise é crucial para o avanço do conhecimento sobre as bases moleculares das neoplasias e para a identificação de marcadores moleculares para uso em diagnóstico, desenho de novos medicamentos em terapias anti-tumorais. Este trabalho tem como objetivos o desenvolvimento de modelos de análise desses dados, propondo uma nova forma de normalização de dados pr

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18

Kapur, Karen Anita. "Low-level analysis of microarray probes on exon-targeting microarrays : modeling background, gene expression and cross-hybridization /." May be available electronically:, 2008. http://proquest.umi.com/login?COPT=REJTPTU1MTUmSU5UPTAmVkVSPTI=&clientId=12498.

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19

Morales, Narváez Eden. "Nanomaterials based microarray platforms for biodetection." Doctoral thesis, Universitat Politècnica de Catalunya, 2013. http://hdl.handle.net/10803/286742.

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Analytical disciplines are an important field for the progress of healthcare and medicine. In fact the technologies related to analytical disciplines may reveal important information for early diagnosis, treatment of diseases, food safety and environmental monitoring. In this regard, novel advances in analytical disciplines are highly desired. As a promising tool, biosensors are useful systems that enable the detection of agents with diagnostic interest. Since nanotechnology enables the manipulation and control at the nanoscale, biosensors based on nanotechnology offer powerful capabilities to

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20

Fellenberg, Kurt. "Storage and analysis of microarray data." [S.l.] : [s.n.], 2002. http://deposit.ddb.de/cgi-bin/dokserv?idn=964718839.

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21

Hare, Brian K. Dinakarpandian Deendayal. "Feature selection in DNA microarray analysis." Diss., UMK access, 2004.

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Thesis (M.S.)--School of Computing and Engineering. University of Missouri--Kansas City, 2004.<br>"A thesis in computer science." Typescript. Advisor: D. Dinakarpandian. Vita. Title from "catalog record" of the print edition Description based on contents viewed Feb. 24, 2006. Includes bibliographical references (leaves 81-86 ). Online version of the print edition.

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22

Hultin, Emilie. "Genetic Sequence Analysis by Microarray Technology." Doctoral thesis, Stockholm : School of Biotechnology, Royal Institute of Technology, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-4330.

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23

Lindroos, Katarina. "Accessing Genetic Variation by Microarray Technology." Doctoral thesis, Uppsala : Acta Universitatis Upsaliensis : Univ.-bibl. [distributör], 2002. http://publications.uu.se/theses/91-554-5251-5/.

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24

Liljedahl, Ulrika. "Microarray Technology for Genotyping in Pharmacogenetics." Doctoral thesis, Uppsala : Acta Universitatis Upsaliensis : Univ.-bibl. [distributör], 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-4222.

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25

Zhou, Ye. "Microcontact printing for protein microarray applications /." Linköping : Univ, 2004. http://www.bibl.liu.se/liupubl/disp/disp2004/tek886s.pdf.

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26

Eijsden, Rudy Gerardus Elisabeth van. "Microarray analysis of oxidative phosphorylation disorders." [Maastricht] : Maastricht : Maastricht University ; University Library, Universiteit Maastricht [host], 2008. http://arno.unimaas.nl/show.cgi?fid=10708.

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27

Peeters, Justine Kate. "Microarray bioinformatics and applications in oncology." [S.l.] : Rotterdam : [The Author] ; Erasmus University [Host], 2008. http://hdl.handle.net/1765/12618.

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28

Ronksley, Jonathan N. "Microarray Analysis of P19CL6 Cardiac Differentiation." Thesis, University of Nottingham, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.518881.

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29

Huang, Liping. "STATISTICAL METHODS IN MICROARRAY DATA ANALYSIS." UKnowledge, 2009. http://uknowledge.uky.edu/gradschool_diss/795.

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This dissertation includes three topics. First topic: Regularized estimation in the AFT model with high dimensional covariates. Second topic: A novel application of quantile regression for identification of biomarkers exemplified by equine cartilage microarray data. Third topic: Normalization and analysis of cDNA microarray using linear contrasts.

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30

Lau, Kin-chong, and 劉健莊. "Microarray-based investigations of genetic diseases." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2011. http://hub.hku.hk/bib/B45894760.

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31

Hsu, Jessie. "Outcome-Driven Clustering of Microarray Data." Thesis, Harvard University, 2012. http://dissertations.umi.com/gsas.harvard:10410.

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The rapid technological development of high-throughput genomics has given rise to complex high-dimensional microarray datasets. One strategy for reducing the dimensionality of microarray experiments is to carry out a cluster analysis to ﬁnd groups of genes with similar expression patterns. Though cluster analysis has been studied extensively, the clinical context in which the analysis is performed is usually considered separately if at all. However, allowing clinical outcomes to inform the clustering of microarray data has the potential to identify gene clusters that are more useful for descri

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32

Brandt, Regine, Robert Grützmann, Andrea Bauer, et al. "DNA microarray analysis of pancreatic malignancies." Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2014. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-136556.

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Pancreatic ductal adenocarcinoma (PDAC) has an extremely poor prognosis. To improve the prognosis, novel molecular markers and targets for earlier diagnosis and adjuvant and/or neoadjuvant treatment are needed. Recent advances in human genome research and high-throughput molecular technologies make it possible to cope with the molecular complexity of malignant tumors. With DNA array technology, mRNA expression levels of thousand of genes can be measured simultaneously in a single assay. As several studies using microarrays in PDAC have already been published, this review attempts to compare th

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33

Jen, Chih-Hung. "Microarray data analysis for Arabidopsis thaliana." Thesis, University of Leeds, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.417754.

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34

Rogers, Simon David. "Machine learning techniques for microarray analysis." Thesis, University of Bristol, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.409426.

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35

Pearson, Richard Peter. "Developing and benchmarking microarray analysis methods." Thesis, University of Manchester, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.549322.

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36

Caygill, J. S. "Microarray sensors for detecting airborne explosives." Thesis, Cranfield University, 2011. http://dspace.lib.cranfield.ac.uk/handle/1826/9174.

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Due to the enhanced level of national security currently required due to the possibility of terrorist attack, monitoring devices for trace levels of explosive materials are now of the upmost importance. One such method that offers a possible route towards the development of a system for the detection of such analytes is via an electrochemical regime, coupled to the use of disposable sensor technology. Within this study, the use of modified carbon screen-printed sensors for the detection and analysis of such analytes of importance has been investigated. The modification of the base carbon subst

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37

Khodiyar, Varsha Kumari. "Microarray profiling of inflammatory bowel disease." Thesis, University of Leicester, 2002. http://hdl.handle.net/2381/29415.

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In this study of inflammatory bowel diseases (IBD, i.e. Crohn's disease and ulcerative colitis), the gene transcription profile of colonic IBD resection specimens were analysed by oligonucleotide microarray analysis. A total of 33,625 genes were profiled across 23 colonic mucosa samples; 5 involved Crohn's disease, 4 uninvolved Crohn's disease, 5 involved ulcerative colitis, 3 uninvolved ulcerative colitis and 6 samples from macroscopically normal areas of colorectal cancer resections (controls). A number of data-mining tools, encompassing clustering (e.g. hierarchical & K-means) and matrix-ba

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38

Amaral, Telmo. "Analysis of breast tissue microarray spots." Thesis, University of Dundee, 2010. https://discovery.dundee.ac.uk/en/studentTheses/0a83915d-2f11-4b89-9c24-8dc3c15346f2.

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Tissue microarrays (TMAs) are a high-throughput technique that facilitates the survey of very large numbers of tumours, important both in clinical and research applications. However, the assessment of stained TMA sections is laborious and still needs to be carried manually, constituting a bottleneck in the pathologist?s work-flow. This process is also prone to perceptual errors and observer variability.Thus, there is strong motivation for the development of automated quantitative analysis of TMA image data. The analysis of breast TMA sections subjected to nuclear immunostaining begins with the

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39

Brandt, Regine, Robert Grützmann, Andrea Bauer, et al. "DNA microarray analysis of pancreatic malignancies." Karger, 2004. https://tud.qucosa.de/id/qucosa%3A27711.

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Pancreatic ductal adenocarcinoma (PDAC) has an extremely poor prognosis. To improve the prognosis, novel molecular markers and targets for earlier diagnosis and adjuvant and/or neoadjuvant treatment are needed. Recent advances in human genome research and high-throughput molecular technologies make it possible to cope with the molecular complexity of malignant tumors. With DNA array technology, mRNA expression levels of thousand of genes can be measured simultaneously in a single assay. As several studies using microarrays in PDAC have already been published, this review attempts to compare th

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40

Bertone, Paul. "Microarray Approaches to Experimental Genome Annotation." Diss., Yale University, 2005. http://hdl.handle.net/10919/71577.

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This work describes the development and application of genomic DNA tiling arrays: microarrays designed to represent all of the DNA comprising a chromosome or other genomic locus, regardless of the genes that may be annotated in the region of interest. Because tiling arrays are intended for the unbiased interrogation of genomic sequence, they enable the discovery of novel functional elements beyond those described by existing gene annotation. This is of particular importance in mapping the gene structures of higher eukaryotes, where combinatorial exon usage produces rare splice variants or isof

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41

Teixeira, Bellina Ribau. "Computational methods for microarray data analysis." Master's thesis, Universidade de Aveiro, 2009. http://hdl.handle.net/10773/3989.

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Mestrado em Engenharia de Computadores e Telemática<br>Os microarrays de ácido desoxirribonucleico (ADN) são uma importante tecnologia para a análise de expressão genética. Permitem medir o nível de expressão de genes em várias amostras para, por exemplo, identificar genes cuja expressão varia com a administração de determinado medicamento. Um slide de microarray mede o nível de expressão de milhares de genes numa amostra ao mesmo tempo e uma experiência pode usar vários slides, surgindo assim muitos dados que é preciso processar e analisar, com recurso a meios informáticos. Esta dissertação

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42

Sehlstedt, Jonas. "Replacing qpcr non-detects with microarray expression data : An initialized approach towards microarray and qPCR data integration." Thesis, Högskolan i Skövde, Institutionen för biovetenskap, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-15790.

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Gene expression analysis can be performed by a number of methods. One of the most common methods is using relative qPCR to assess the relative expression of a determined set of genes compared to a reference gene. Analysis methods benefits from an as homogeneous sample set as possible, as great variety in original sample disease status, quality, type, or distribution may yield an uneven base expression between replicates. Additionally normalization of qPCR data will not work if there are missing values in the data. There are methods for handling non-detects (i.e. missing values) in the data, w

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43

Szeto, Lap Keung. "Clustering analysis of microarray gene expression data /." access full-text access abstract and table of contents, 2005. http://libweb.cityu.edu.hk/cgi-bin/ezdb/thesis.pl?mphil-it-b19885817a.pdf.

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Thesis (M.Phil.)--City University of Hong Kong, 2005.<br>"Submitted to Department of Computer Engineering and Information Technology in partial fulfillment of the requirements for the degree of Master of Philosophy" Includes bibliographical references (leaves 70-79)

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44

Botella, Pérez Cristina. "Multivariate classification of gene expression microarray data." Doctoral thesis, Universitat Rovira i Virgili, 2010. http://hdl.handle.net/10803/9046.

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L'expressiódels gens obtinguts de l'anàliside microarrays s'utilitza en molts casos, per classificar les cèllules. En aquestatesi, unaversióprobabilística del mètodeDiscriminant Partial Least Squares (p-DPLS)s'utilitza per classificar les mostres de les expressions delsseus gens. p-DPLS esbasa en la regla de Bayes de la probabilitat a posteriori. Aquestsclassificadorssónforaçats a classficarsempre.Per superaraquestalimitaciós'haimplementatl'opció de rebuig.Aquestaopciópermetrebutjarlesmostresamb alt riscd'errors de classificació (és a dir, mostresambigüesi outliers).Aquestaopció de rebuigcombi

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45

Lee, Kyeong Eun. "Bayesian models for DNA microarray data analysis." Diss., Texas A&M University, 2005. http://hdl.handle.net/1969.1/2465.

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Selection of signi?cant genes via expression patterns is important in a microarray problem. Owing to small sample size and large number of variables (genes), the selection process can be unstable. This research proposes a hierarchical Bayesian model for gene (variable) selection. We employ latent variables in a regression setting and use a Bayesian mixture prior to perform the variable selection. Due to the binary nature of the data, the posterior distributions of the parameters are not in explicit form, and we need to use a combination of truncated sampling and Markov Chain Monte Carlo (MCMC)

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46

Lönnstedt, Ingrid. "Empirical Bayes Methods for DNA Microarray Data." Doctoral thesis, Uppsala University, Department of Mathematics, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-5865.

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<p>cDNA microarrays is one of the first high-throughput gene expression technologies that has emerged within molecular biology for the purpose of functional genomics. cDNA microarrays compare the gene expression levels between cell samples, for thousands of genes simultaneously. </p><p>The microarray technology offers new challenges when it comes to data analysis, since the thousands of genes are examined in parallel, but with very few replicates, yielding noisy estimation of gene effects and variances. Although careful image analyses and normalisation of the data is applied, traditional metho

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47

Kocabas, Fahri. "Knowledge Discovery In Microarray Data Of Bioinformatics." Phd thesis, METU, 2012. http://etd.lib.metu.edu.tr/upload/12615090/index.pdf.

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This thesis analyzes major microarray repositories and presents a metadata framework both to address the current issues and to promote the main operations such as knowledge discovery, sharing, integration, and exchange. The proposed framework is demonstrated in a case study on real data and can be used for other high throughput repositories in biomedical domain. Not only the number of microarray experimentation increases, but also the size and complexity of the results rise in response to biomedical inquiries. And, experiment results are significant when examined in a batch and placed in a bio

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48

Li, Ying. "Efficient Combinatorial Algorithms for DNA Microarray Design." Thesis, University of Liverpool, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.490907.

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The advent of efficient genome sequencing tools and high-throughput experimental biotechnology has led to enonnous progress in the life science. DNA microarray is among the most important innovations. It allows to measure the expression for thousands of genes simultaneously by analysing the hybridisation data. Such measurements have been proved to be invaluable in understanding the development of diseases such as cancer. However, the analysis of data is non-trivial since the hybridisation data relies on the quality of DNA microarray. High quality DNA microarray will lead to more efficient hybr

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Moertel, Luke Paul Frank, and mobileluke@hotmail com /. Luke Moertel@qimr edu au. "Microarray Analysis of the Schistosoma japonicum Transcriptome." Central Queensland University. Chemical and Biomedical Sciences, 2007. http://library-resources.cqu.edu.au./thesis/adt-QCQU/public/adt-QCQU20070705.120939.

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Schistosomiasis, a disease of humans caused by helminth parasites of the genus Schistosoma, kills 200 to 500 thousand people annually, endangering over 600 million people world-wide with 200 million people infected in 2003 [1, 2]. Three species of schistosome are primarily responsible for human infections, namely, Schistosoma haematobium, endemic to Africa, India, and the Middle East, S. mansoni, endemic to Africa / South America, and S. japonicum endemic to China and the Philippines [3]. The major pathological effects of schistosomiasis result from the deposition of parasite ova in human tiss

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Eijssen, Lars Maria Theo. "Analysis of microarray gene expression data sets." [Maastricht : Maastricht : Universiteit Maastricht] ; University Library, Universiteit Maastricht [host], 2006. http://arno.unimaas.nl/show.cgi?fid=6830.

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