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Dissertations / Theses on the topic 'Gene expression analysis'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Curtis, R. K. "Control analysis of gene expression." Thesis, University of Cambridge, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.598230.

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This thesis describes the development of the application of modular regulation analysis, a subset of metabolic control analysis to microarray data. Microarray experiments measure complex changes in the abundance of many mRNAs under different conditions. Current analysis methods, such as clustering, cannot distinguish between direct and indirect effects on expression, or calculate the relative importance of mRNAs in effecting responses. Modular regulation analysis of microarray data reveals and quantifies which mRNA changes are important for cellular responses. The mRNAs are clustered, then ho

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2

Johansson, Karin. "Analysis of immunoglobulin gene expression focus on Oct2 /." Lund : Dept. of Cell and Molecular Biology, Lund University, 1995. http://catalog.hathitrust.org/api/volumes/oclc/39776663.html.

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3

Liebermeister, Wolfram. "Analysis of optimal differential gene expression." Doctoral thesis, [S.l. : s.n.], 2004. http://deposit.ddb.de/cgi-bin/dokserv?idn=97257347X.

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4

Muthukaruppan, Anita. "Gene expression analysis in breast cancer." Thesis, University of Auckland, 2011. http://hdl.handle.net/2292/6997.

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Breast cancer is a leading cause of malignancy worldwide. Improvements to gene expression profiling technology have resulted in the identification of many prognostic and predictive gene expression signatures for breast cancer. Whilst some of these signatures are being developed commercially, only two prognostic signatures: MammaPrint and Oncotype DX, are currently being validated in clinical trials. Many of these gene expression signatures require independent validation and the underlying biology behind these signatures remains unclear. The aim of this thesis is to identify key molecular pathw

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5

Sohler, Florian. "Contextual Analysis of Gene Expression Data." Diss., lmu, 2006. http://nbn-resolving.de/urn:nbn:de:bvb:19-55936.

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6

Siangphoe, Umaporn. "META-ANALYSIS OF GENE EXPRESSION STUDIES." VCU Scholars Compass, 2015. http://scholarscompass.vcu.edu/etd/4040.

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Combining effect sizes from individual studies using random-effects models are commonly applied in high-dimensional gene expression data. However, unknown study heterogeneity can arise from inconsistency of sample qualities and experimental conditions. High heterogeneity of effect sizes can reduce statistical power of the models. We proposed two new methods for random effects estimation and measurements for model variation and strength of the study heterogeneity. We then developed a statistical technique to test for significance of random effects and identify heterogeneous genes. We also propo

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7

Yeung, Ka Yee. "Cluster analysis of gene expression data /." Thesis, Connect to this title online; UW restricted, 2001. http://hdl.handle.net/1773/6986.

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8

Boonjakuakul, Jenni Kim. "Analysis of Helicobacter pylori gene expression /." For electronic version search Digital dissertations database. Restricted to UC campuses. Access is free to UC campus dissertations, 2003. http://uclibs.org/PID/11984.

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9

Thamrin, Sri Astuti. "Bayesian survival analysis using gene expression." Thesis, Queensland University of Technology, 2013. https://eprints.qut.edu.au/62666/1/Sri_Astuti_Thamrin_Thesis.pdf.

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This thesis developed and applied Bayesian models for the analysis of survival data. The gene expression was considered as explanatory variables within the Bayesian survival model which can be considered the new contribution in the analysis of such data. The censoring factor that is inherent of survival data has also been addressed in terms of its impact on the fitting of a finite mixture of Weibull distribution with and without covariates. To investigate this, simulation study were carried out under several censoring percentages. Censoring percentage as high as 80% is acceptable here as the w

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10

Campbell, Lisa Jane. "Gene expression analysis of telomerase related genes in myeloid malignancy." Thesis, Open University, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.578282.

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Telomere shortening and an increased telomerase activity are associated with poor prognosis and disease progression in many cancers. In Chronic Myeloid Leukaemia (CML) telomere shortening has a strong correlation with disease progression. Expression of hTERT, the catalytic component of telomerase, was evaluated in the CD34+ cells of CML patients. This revealed that expression of hTERT was significantly reduced in chronic phase CML and decreased with disease progression to accelerated phase and blast crisis. .It could therefore be concluded that reduced hTERT expression contributes to reduced t

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11

Wang, Dali. "Adaptive Double Self-Organizing Map for Clustering Gene Expression Data." Fogler Library, University of Maine, 2003. http://www.library.umaine.edu/theses/pdf/WangD2003.pdf.

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12

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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13

Chipindirwi, Simbarashe. "Analysis of a simple gene expression model." Thesis, Lethbridge, Alta. : University of Lethbridge, Dept. of Chemistry and Biochemistry, c2012, 2012. http://hdl.handle.net/10133/3251.

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Gene expression is random owing to the low copy numbers of molecules in a living cell and the best way to study it is by use of a stochastic method, specifically the chemical master equation. The method is used here to derive analytically the invariant probability distributions, and expressions for the moments and noise strength for a simple gene model without feedback. Sensitivity analysis, emphasizing particularly the dependence of the probability distributions, the moments, and noise strength is carried out using Metabolic Control Analysis, which uses control coefficients that measure the r

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14

Reynolds, Robert. "Gene Expression Data Analysis Using Fuzzy Logic." Fogler Library, University of Maine, 2001. http://www.library.umaine.edu/theses/pdf/REynoldsR2001.pdf.

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15

Begg, Alison Jane. "Analysis of NMDA receptor regulated gene expression." Thesis, University of Edinburgh, 2005. http://hdl.handle.net/1842/25053.

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Mutation of two NMDA receptor complex proteins, PSD95 and SynGAP, results in altered phenotypes in NMDA dependent phenomena. As components of the receptor complex, necessary for NMDA mediated signalling, mutation of these proteins may alter pathways that regulate gene expression. Affymetrix microarray analysis of RNA from PSD95<sup>-/-</sup> forebrain and SynGAP<sup>-/-</sup> hippocampi, compared to wildtype samples, revealed significant changes, greater than 1.5 fold, in a limited numbers of genes. Of the 12000 transcripts analysed 0.22% were significantly altered in PSD95 mutant tissue and 0

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16

Haghighi, Maryam. "Graph-theoretic analysis of gene expression networks." Thesis, University of Ottawa (Canada), 2007. http://hdl.handle.net/10393/27460.

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We use graph theory to model a database of gene expression levels and provide a tool that can assist in designing biological experiments which could help to better understand the interactions between genes. The data was provided by StemBase (http://www.stembase.ca). We model a portion of this database as a graph, and study some parameters on it that may be biologically relevant. We include theoretical discussion of the parameters, and presentation of algorithms for their computation. The focus is on structural properties of the graph; thus, we investigate the graph's bipartiteness, connected c

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17

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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18

Gale, Matthew. "Parallel computing for Gene Expression Data Analysis /." Leeds : University of Leeds, School of Computer Studies, 2008. http://www.comp.leeds.ac.uk/fyproj/reports/0708/Gale.pdf.

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19

Dodeweerd, Anne-Marie van. "Comparative analysis of gene expression in plants." Thesis, University of East Anglia, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.327512.

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20

Seow, Choon Sheong. "Analysis of gene expression in tumour immortalisation." Thesis, University of Aberdeen, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.251848.

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Cellular senescence is an irreversible growth-arrested state seen in primary human cells after a finite number of cell divisions both in culture and <i>in vivo</i>. The escape from senescence to immortalisation is often thought to be a prerequisite for carcinogenesis. Many changes in senescent cells are consistent with changes in tissue and organ function with age. I used serial analysis of gene expression (SAGE) to analyse global gene expression profiles in senescent and early passage human foetal fibroblasts (hff). A total of over 20,000 SAGE tags were sequenced and characterised, correspond

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21

Duggar, Keith Howard 1976. "Modeling and analysis of gene expression arrays." Thesis, Massachusetts Institute of Technology, 2004. http://hdl.handle.net/1721.1/29445.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, 2004.<br>Includes bibliographical references (p. 65-66).<br>Gene expression arrays are a technology used to measure quantities of messenger ribonucleic acid (mRNA). Application of the technology involves a variety of physical processes beginning with the acquisition of mRNA samples and ending with the fluorescence imaging of a gene expression array. This thesis examines these physical processes, develops a mechanistic model, and derives the analysis procedure based on the model. Chief advantages of this appr

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22

Barnett, John D. (John Derek) 1970. "Convex matrix factorization for gene expression analysis." Thesis, Massachusetts Institute of Technology, 2004. http://hdl.handle.net/1721.1/30098.

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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2004.<br>Includes bibliographical references (p. 68-71).<br>A method is proposed for gene expression analysis relying upon convex matrix factorization (CMF). In CMF, one of the matrix factors has a convexity constraint, that is, each row is nonnegative and sums to one, and hence can be interpreted as a probability distribution. This is motivated biologically by expression data resulting from a mixture of different cell types. This thesis investigates implementing CMF with various constra

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23

Suwanwela, Jaijam. "Integrative genetics analysis of cartilage gene expression." Diss., Restricted to subscribing institutions, 2009. http://proquest.umi.com/pqdweb?did=1872166161&sid=2&Fmt=2&clientId=1564&RQT=309&VName=PQD.

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24

Gabrovska, Plamena N. "Gene Expression Analysis in Human Breast Cancer." Thesis, Griffith University, 2012. http://hdl.handle.net/10072/367577.

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Breast Cancer is the most commonly diagnosed cancer in women, with more than 1.2 million women diagnosed annually worldwide. It is also a frequently fatal disease and remains difficult to treat, despite advances in all facets of cancer management. While a number of genetic mutations have been identified in human breast cancers, he specific combinations of the mutations required in concert for formation of a breast carcinoma remains unknown, making precise detection or prognostic predictions impossible. Although estrogen receptor (ER) status is predictive of response to hormonal treatments, th

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25

Summers, Ryan Michael. "Gene Expression Analysis of Immobilized Saccharomyces Cerevisiae." DigitalCommons@USU, 2008. https://digitalcommons.usu.edu/etd/68.

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Immobilization is an effective method to increase ethanol production, as proven by previous research. Results almost exclusively demonstrate an increase in ethanol production by and decrease in reproduction rate of immobilized Saccharomyces cerevisiae cells. Recently, research has been conducted to determine the cause of this change. The extreme variance in results due to lack of technology makes it difficult to determine the cellular changes induced by immobilization. With the advent of new technology, specifically gene expression analysis, the RNA content of cells can be easily and rapid

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26

Simcock, Wendy. "Parallel Analysis of Gene Expression: Bone Cells as a Model System." Thesis, Griffith University, 2005. http://hdl.handle.net/10072/365317.

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The use of comparative gene expression techniques has expanded considerably in recent years, especially with advances in microarray technology. In this project, a number of these techniques have been used to identify genes worthy of further research as potential mediators of bone cell differentiation and function. Bone is a tissue with many potential as yet unidentified regulatory molecules. The skeleton is constantly undergoing replacement, with old bone being degraded by osteoclasts, bone resorbing cells derived from the haematopoietic lineage, and replaced with new bone by osteoblasts, bone

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27

Li, Wei. "Analyzing Gene Expression Data in Terms of Gene Sets: Gene Set Enrichment Analysis." Digital Archive @ GSU, 2009. http://digitalarchive.gsu.edu/math_theses/79.

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The DNA microarray biotechnology simultaneously monitors the expression of thousands of genes and aims to identify genes that are differently expressed under different conditions. From the statistical point of view, it can be restated as identify genes strongly associated with the response or covariant of interest. The Gene Set Enrichment Analysis (GSEA) method is one method which focuses the analysis at the functional related gene sets level instead of single genes. It helps biologists to interpret the DNA microarray data by their previous biological knowledge of the genes in a gene set. GSEA

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28

Gesteira, Costa Filho Ivan. "Comparative analysis of clustering methods for gene expresion data." Universidade Federal de Pernambuco, 2003. https://repositorio.ufpe.br/handle/123456789/2538.

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Made available in DSpace on 2014-06-12T15:59:06Z (GMT). No. of bitstreams: 2 arquivo4839_1.pdf: 1378221 bytes, checksum: f1a933734804959bb52fd2eef936641b (MD5) license.txt: 1748 bytes, checksum: 8a4605be74aa9ea9d79846c1fba20a33 (MD5) Previous issue date: 2003<br>Large scale approaches, namely proteomics and transcriptomics, will play the most important role of the so-called post-genomics. These approaches allow experiments to measure the expression of thousands of genes from a cell in distinct time points. The analysis of this data can allow the the understanding of gene function and gene

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29

Jadhav, Trishul. "Knowledge Based Gene Set analysis (KB-GSA) : A novel method for gene expression analysis." Thesis, University of Skövde, School of Life Sciences, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-4352.

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<p>Microarray technology allows measurement of the expression levels of thousand of genes simultaneously. Several gene set analysis (GSA) methods are widely used for extracting useful information from microarrays, for example identifying differentially expressed pathways associated with a particular biological process or disease phenotype. Though GSA methods like Gene Set Enrichment Analysis (GSEA) are widely used for pathway analysis, these methods are solely based on statistics. Such methods can be awkward to use if knowledge of specific pathways involved in particular biological processes a

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30

Cheung, Kwan-lok. "Analysis of lacZ gene expression patterns of a Hoxb3[lacZ] mouse mutant during early development /." View the Table of Contents & Abstract, 2005. http://sunzi.lib.hku.hk/hkuto/record/B3508571X.

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31

Morgan, Daniel Colin. "A Gene Co-Expression Network Mining Approach for Differential Expression Analysis." The Ohio State University, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=osu1416989632.

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32

Wang, Yan, and 王嫣. "Bioinformatics analysis of genetic and epigenetic factors regulating gene expression." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2015. http://hdl.handle.net/10722/208546.

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33

Llewelyn, Jenefer Kirstin. "Analysis of gene expression in squamous cell carcinomas." Thesis, King's College London (University of London), 2006. https://kclpure.kcl.ac.uk/portal/en/theses/analysis-of-gene-expression-in-squamous-cell-carcinomas(4ce3ae48-c239-4bc0-918e-e4aa691bd0d2).html.

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34

Andersson, Tove. "Approaches to differential gene expression analysis in atherosclerosis." Doctoral thesis, KTH, Biotechnology, 2002. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-3400.

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<p>Todays rapid development of powerful tools for geneexpression analysis provides unprecedented resources forelucidating complex molecular events.</p><p>The objective of this workhas been to apply, combine andevaluate tools for analysis of differential gene expressionusing atherosclerosis as a model system. First, an optimisedsolid-phase protocol for representational difference analysis(RDA) was applied to two<i>in vitro</i>model systems. Initially, The RDA enrichmentprocedure was investigated by shotgun cloning and sequencing ofsuccessive difference products. In the subsequent steps,combina

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35

Lundell, Simon. "Modelling Gene Expression during Ontogenetic Differentiation." Thesis, University of Skövde, Department of Computer Science, 2001. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-590.

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<p>Various types of recurrent neural networks have been used as models for the regulatory relationships between genes. The neural network is trained on the data from micro-array techniques, each gene corresponds to a neuron in the network. The data from the micro-array technologies has numerous genes, but usually involves few samples, this makes the network heavily under-determined. In this work we will propose a method that can cope with the poorness of the data. We will use a Hopfield-type neural network to model the ontogenetic differentiation of female honeybees. A method that identifies t

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36

Venet, David. "Algorithms for the analysis of gene expression data." Doctoral thesis, Universite Libre de Bruxelles, 2004. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/211127.

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High-throughput gene expression data have been generated on a large scale by biologists.<p>The thesis describe a set of tools for the analysis of such data. It is specially gearded towards microarray data.<br>Doctorat en sciences appliquées<br>info:eu-repo/semantics/nonPublished

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37

LaPointe, Lawrence C., and larry lapointe@flinders edu au. "Gene expression biomarkers for colorectal neoplasia." Flinders University. School of Medicine, 2009. http://catalogue.flinders.edu.au./local/adt/public/adt-SFU20091011.090028.

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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 phenot

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38

Boräng, Stina. "Subtracted Approaches to Gene Expression Analysis in Atherosclerosis." Doctoral thesis, KTH, Biotechnology, 2003. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-3684.

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<p>Gene expression analysis has evolved as an extensive toolfor elucidation of various biological and molecular eventsoccurring in different organisms. A variety of techniques andsoftware tools have been developed to enable easier and morerapid means of exploring the genetic information. A moreeffective approach than exploring the whole content of genesexpressed under certain conditions is to study fingerprintassays or to use subtracted cDNA libraries to identify onlydifferentially expressed genes.</p><p>The objective for the work in this thesis has been toexplore differentially expressed gene

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39

Denny, Paul. "Molecular analysis of gene expression in rat brain." Thesis, Imperial College London, 1991. http://hdl.handle.net/10044/1/46744.

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40

Laurell, Cecilia. "Microarray Based Gene Expression Analysis in Cancer Research." Doctoral thesis, Stockholm : School of Biotechnology, Royal Institute of Technology, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-4244.

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41

Łuksza, Marta [Verfasser]. "Cluster statistics and gene expression analysis / Marta Łuksza." Berlin : Freie Universität Berlin, 2012. http://d-nb.info/1026883113/34.

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42

Nichol, Donna. "Analysis of receptor interacting protein (RIP140) gene expression." Thesis, Imperial College London, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.434341.

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43

Zien, Alexander [Verfasser]. "Computational Analysis of Gene Expression Data / Alexander Zien." Aachen : Shaker, 2004. http://d-nb.info/1170544967/34.

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44

Prashar, Ankush. "Arabidopsis QTL analysis using stairs and gene expression." Thesis, University of Birmingham, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.435316.

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45

Sarma, Subrot. "Gene expression analysis in the developing human telencephalon." Thesis, University of Newcastle Upon Tyne, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.443196.

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46

Huang, Andrew Douglas. "Computational analysis of gene expression in complex disease." Diss., Georgia Institute of Technology, 2014. http://hdl.handle.net/1853/54257.

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Cardiovascular disease (CVD) causes 45% of on-duty firefighter fatalities, a high fraction even when compared to the risk of CVD found in other first-responder professions like police work and emergency medical services. Monitoring and managing firefighter cardiac health is important for both individual health and public safety. In our study, we are interested in assessing the utility of the most commonly used risk assessment scoring, known as the Framingham Risk Score, in evaluating the atherosclerotic risk in asymptomatic firefighters. To this end we determined FRS for 159 male firefighters

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47

Udall, Joshua, Lex Flagel, Foo Cheung, et al. "Spotted cotton oligonucleotide microarrays for gene expression analysis." BioMed Central, 2007. http://hdl.handle.net/10150/610000.

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BACKGROUND:Microarrays offer a powerful tool for diverse applications plant biology and crop improvement. Recently, two comprehensive assemblies of cotton ESTs were constructed based on three Gossypium species. Using these assemblies as templates, we describe the design and creation and of a publicly available oligonucleotide array for cotton, useful for all four of the cultivated species.RESULTS:Synthetic oligonucleotide probes were generated from exemplar sequences of a global assembly of 211,397 cotton ESTs derived from >50 different cDNA libraries representing many different tissue types a

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Borris, Douglas J. "Temporal Analysis of Bacteriophage Felix O1 Gene Expression." Thesis, Virginia Tech, 2002. http://hdl.handle.net/10919/35791.

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Bacteriophage Felix O1, also known as enterobacteria phage O1, has been used to type Salmonella Typhi and is an excellent candidate for use in bioremedial and therapeutic applications. It has extremely high intra-species specificity and is strictly virulent in nature, unable to undergo lysogeny. To facilitate the development of the bacteriophage for use in these areas, the full sequence of the genome had been elucidated previously. In this work, identification and classification of functional coding sequences via reverse transcriptase-polymerase chain reaction was performed. <p>All of the

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Wang, Yu. "Fuzzy clustering models for gene expression data analysis." Thesis, Northumbria University, 2014. http://nrl.northumbria.ac.uk/21438/.

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With the advent of microarray technology, it is possible to monitor gene expression of tens of thousands of genes in parallel. In order to gain useful biological knowledge, it is necessary to study the data and identify the underlying patterns, which challenges the conventional mathematical models. Clustering has been extensively used for gene expression data analysis to detect groups of related genes. The assumption in clustering gene expression data is that co-expression indicates co-regulation, thus clustering should identify genes that share similar functions. Microarray data contains plen

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Toyota, Kentaro. "Molecular analysis of C3 phosphoenolpyruvate carboxylase gene expression." Kyoto University, 2002. http://hdl.handle.net/2433/149506.

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Kyoto University (京都大学)<br>0048<br>新制・課程博士<br>博士(農学)<br>甲第9781号<br>農博第1293号<br>新制||農||852(附属図書館)<br>学位論文||H14||N3712(農学部図書室)<br>UT51-2002-M159<br>京都大学大学院農学研究科応用生命科学専攻<br>(主査)教授佐藤文彦, 教授關谷次郎, 教授泉井桂<br>学位規則第4条第1項該当

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