Rozprawy doktorskie na temat „Differential gene expression”
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Al-Lawati, Sabah Ali Redha. "Differential gene expression in schizophrenia". Thesis, Imperial College London, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.420028.
Pełny tekst źródłaSweeney, Glen E. "Differential gene expression in Physarum". Thesis, University of Leicester, 1987. http://hdl.handle.net/2381/35166.
Pełny tekst źródłaFung, Lai-fan. "Differential gene expression in nasopharyngeal carcinoma /". Hong Kong : University of Hong Kong, 1999. http://sunzi.lib.hku.hk/hkuto/record.jsp?B20604609.
Pełny tekst źródłaLiebermeister, Wolfram. "Analysis of optimal differential gene expression". Doctoral thesis, [S.l. : s.n.], 2004. http://deposit.ddb.de/cgi-bin/dokserv?idn=97257347X.
Pełny tekst źródła馮麗芬 i Lai-fan Fung. "Differential gene expression in nasopharyngeal carcinoma". Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1999. http://hub.hku.hk/bib/B31220824.
Pełny tekst źródła方佩儀 i Pui-yee Fong. "Differential gene expression in gestational trophoblastic disease". Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2001. http://hub.hku.hk/bib/B31224362.
Pełny tekst źródłaHu, Yanmin. "Differential gene expression in dormant mycobacterium tuberculosis". Thesis, St George's, University of London, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.325140.
Pełny tekst źródłaGhate, Aditée. "The opioid system and differential gene expression". Université Louis Pasteur (Strasbourg) (1971-2008), 2006. http://www.theses.fr/2006STR13019.
Pełny tekst źródłaThe opioid system consists of three G-protein coupled receptors, mu, delta, and kappa, which are stimulated by a family of endogenous opioid peptides like beta-endorphin and exogenous ligands such as morphine. It is believed that the repeated opiate administration alters gene expression in different brain regions of rodents, an effect which may contribute to plastic changes associated with addictive behaviour. Oligonucleotide and cDNA microarrays are the two most commonly used methods to profile the expression of thousands of genes in parallel. Gene expression studies performed by microarray analysis or by parallel measurements of the mRNA of multiple candidate genes have become a powerful tool to screen gene expression in the brain after application of drugs of abuse. Studies have shown that the reinforcing properties of morphine, alcohol, cannabinoids and nicotine are abolished or diminished in mice lacking the mu-opioid receptor. The genetic approach therefore highlights mu opioid receptors as convergent molecular switches which mediate reinforcement following direct (eg: morphine) or indirect activation (non-opioid drugs). Use of the mu-opioid receptor knockout mice would therefore help in identifying the genes, downstream of the mu-opioid receptor, that are commonly dysregulated following long term exposure to drugs of abuse. My thesis work involved establishment and use of cDNA and oligonucleotide microarrays screening tools in our laboratory to identify the transcriptional adaptations that occur on activation or in absence of the opioid receptors. I have also characterised obese phenotype observed in the triple opioid receptor knockout mice. Our laboratory is also interested in performing region-specific deletions of the opioid system and is therefore in the process of developing transgenic mice under region-specific promoters. A part of my thesis work also involved searching for region-specific markers for brain areas relevant in drug addiction
Fong, Pui-yee. "Differential gene expression in gestational trophoblastic disease /". Hong Kong : University of Hong Kong, 2001. http://sunzi.lib.hku.hk:8888/cgi-bin/hkuto%5Ftoc%5Fpdf?B23440132.
Pełny tekst źródłaAndersson, 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.
Pełny tekst źródłaTodays rapid development of powerful tools for geneexpression analysis provides unprecedented resources forelucidating complex molecular events.
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 twoin vitromodel systems. Initially, The RDA enrichmentprocedure was investigated by shotgun cloning and sequencing ofsuccessive difference products. In the subsequent steps,combinations of RDA and microarray analysis were used tocombine the selectivity and sensitivity of RDA with thehigh-throughput nature of microarrays. This was achieved byimmobilization of RDA clones onto microarrays dedicated forgene expression analysis in atherosclerosis as well ashybridisation of labelled RDA products onto global microarrayscontaining more than 32,000 human clones. Finally, RDA wasapplied for the investigation of the focal localisation ofatherosclerotic plaques in mice usingin vivotissue samples as starting material.
A large number of differentially expressed clones wereisolated and confirmed by real time PCR. A very diverse rangeof gene fragments was identified in the RDA products especiallywhen they were screened with global microarrays. However, themicroarray data also seem to contain some noise which is ageneral problem using microarrays and should be compensated forby careful verification of the results.
Quite a large number of candidate genes related to theatherosclerotic process were found by these studies. Inparticular several nuclear receptors with altered expression inresponse to oxidized LDL were identified and deserve furtherinvestigation. Extended functional annotation does not liewithin the scope of this thesis but raw data in the form ofnovel sequences and accession numbers of known sequences havebeen made publicly available in GenBank. Parts of the data arealso available for interactive exploration on-line through aninteractive software tool. The data generated thus constitute abase for new hypotheses to be tested in the field ofatherosclerosis.
Keywords:representational difference analysis, geneexpression profiling, microarray analysis, atherosclerosis,foam cell formation
De, las Heras Rachel, i n/a. "Neuronal Differentiation: A Study Into Differential Gene Expression". Griffith University. School of Biomolecular and Biomedical Science, 2003. http://www4.gu.edu.au:8080/adt-root/public/adt-QGU20040225.161725.
Pełny tekst źródłaBjork, Kathe Elizabeth. "Robust identification of differential gene expression and discrimination /". Connect to full text via ProQuest. Limited to UCD Anschutz Medical Campus, 2006.
Znajdź pełny tekst źródłaTypescript. Includes bibliographical references (leaves 237-239). Free to UCDHSC affiliates. Online version available via ProQuest Digital Dissertations;
Neutze, Dana Michelle. "Differential gene expression and progression in cervical neoplasia". Thesis, University of Cambridge, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.614883.
Pełny tekst źródłaChae, Taylor. "SEX-LINKED DIFFERENTIAL GENE EXPRESSION IN CARICA PAPAYA". Miami University / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=miami1533049471465913.
Pełny tekst źródłaDe, las Heras Rachel. "Neuronal Differentiation: A Study Into Differential Gene Expression". Thesis, Griffith University, 2003. http://hdl.handle.net/10072/367735.
Pełny tekst źródłaThesis (PhD Doctorate)
Doctor of Philosophy (PhD)
School of Biomolecular and Biomedical Sciences
Full Text
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.
Pełny tekst źródłaOwens, Sarah Marie. "Differential expression of recent gene duplicates in developmental tissues of Arabidopsis thaliana". Oxford, Ohio : Miami University, 2009. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=miami1250185890.
Pełny tekst źródłaCrampton, Matthew S., i n/a. "Differential Gene Expression in Pathological and Physiological Cardiac Hypertrophy". Griffith University. School of Biomolecular and Biomedical Science, 2006. http://www4.gu.edu.au:8080/adt-root/public/adt-QGU20070104.165826.
Pełny tekst źródłaBrownlie, Laura. "Differential gene expression studies in non-melanoma skin cancer". Thesis, University of Newcastle Upon Tyne, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.323449.
Pełny tekst źródłaCrampton, Matthew S. "Differential Gene Expression in Pathological and Physiological Cardiac Hypertrophy". Thesis, Griffith University, 2006. http://hdl.handle.net/10072/366605.
Pełny tekst źródłaThesis (PhD Doctorate)
Doctor of Philosophy (PhD)
School of Biomolecular and Biomedical Sciences
Full Text
Lam, T. H. Jason. "Differential gene expression associated with phenotypic virulence of mycobacterium tuberculosis". Click to view the E-thesis via HKUTO, 2006. http://sunzi.lib.hku.hk/hkuto/record/B37769005.
Pełny tekst źródłaSaul, Katherine E. "Differential gene expression in Danio rerio during optic nerve regeneration /". View online, 2008. http://ecommons.txstate.edu/bioltad/13.
Pełny tekst źródłaLam, T. H. Jason, i 林梓軒. "Differential gene expression associated with phenotypic virulence of mycobacterium tuberculosis". Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2006. http://hub.hku.hk/bib/B37769005.
Pełny tekst źródłaDi, Capua Daniele-Mario. "Differential gene expression patterns of the vasculature in scleroderma biopsies". Thesis, McGill University, 2010. http://digitool.Library.McGill.CA:8881/R/?func=dbin-jump-full&object_id=92385.
Pełny tekst źródłaLiu, Zhiping. "Differential mucosal gene expression modulates the development of murine colitis". [Ames, Iowa : Iowa State University], 2008.
Znajdź pełny tekst źródłaMcKenna, Louise Agnes. "Differential gene expression in normal and diseased human articular cartilage". Thesis, Imperial College London, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.369207.
Pełny tekst źródłaCarter, Deborah. "Analysis of differential gene expression patterns in non-Hodgkin's lymphoma". Thesis, University of Sheffield, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.301273.
Pełny tekst źródłaBenvenuti, Silvia. "Differential gene expression in rodent embryo fibroblasts upon replicative senescence". Thesis, University College London (University of London), 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.271477.
Pełny tekst źródłaSharp, Matthew George Frederick. "Differential gene expression in benign and malignant human breast tumours". Thesis, University of Leicester, 1992. http://hdl.handle.net/2381/35146.
Pełny tekst źródłaAdam, Emma N. "DIFFERENTIAL GENE EXPRESSION IN EQUINE CARTILAGINOUS TISSUES AND INDUCED CHONDROCYTES". UKnowledge, 2016. http://uknowledge.uky.edu/gluck_etds/25.
Pełny tekst źródłaDimont, Emmanuel. "Methods for the Analysis of Differential Composition of Gene Expression". Thesis, Harvard University, 2015. http://nrs.harvard.edu/urn-3:HUL.InstRepos:14226062.
Pełny tekst źródłaChapman, Tajekesa Kudzaishe Pamacheche. "Regulation of PABP1 function by differential post-translational modification". Thesis, University of Edinburgh, 2016. http://hdl.handle.net/1842/25875.
Pełny tekst źródłaStuiver, Ingrid. "Differential gene expression in TPA responsive and non-responsive mouse fibroblasts". Diss., The University of Arizona, 1992. http://hdl.handle.net/10150/185783.
Pełny tekst źródłaZablocki, Destinee Elizabeth. "Differential Expression of Calsarcin Genes in Orthognathic Surgery Patients with ACTN3 R577X Gene Deviations". Master's thesis, Temple University Libraries, 2016. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/405298.
Pełny tekst źródłaM.S.
Objective: Malocclusion is a complex musculoskeletal trait, with muscle playing an integral role in vertical facial development. A single nucleotide polymorphism (SNP) produces the R577XX nonsense mutation in the alpha-actinin-3 (ACTN3) gene, creating a stop codon and loss of its protein. With loss of ACTN3, alpha-actinin-2 (ACTN2) is upregulated. Calsarcins, known inhibitors of calcineurin activation, preferentially bind ACTN2 leading to a surge in free calcineurin. The increase in calcineurin activity produces the phenotypic shift of fast muscle fibers toward the slow myogenic program seen in the ACTN3 null genotype (Seto et al., 2013). Here, we have tested whether calsarcin gene expression is affected by ACTN3 genotypes in human masseter muscle. Methods: Subjects undergoing orthodontic treatment and orthognathic surgery were recruited from the University of Lille, Department of Oral and Maxillofacial Surgery in Northern France. During the bilateral sagittal split osteotomy, masseter muscle samples were collected from the discarded section of deep anterior superficial masseter muscle, snap frozen, and shipped to Dr. Sciote’s lab at Temple University. RNA from masseter muscle samples was isolated from 41 subjects using TRIzolTM reagent. MYOZ gene expression was quantified by RT-PCR using an adult skeletal muscle reference standard (commercially prepared skeletal muscle RNA; Ambion, Inc), and individual primer-probe sets for MYOZ1, MYOZ2, MYOZ3, and HPRT1 (utilized for normalization of data). ANOVA and unpaired t-tests were used to determine the significance of expression differences between MYOZ genes and by ACTN3 R577X genotypes, as well as by malocclusion classes. Pearson analyses were used to determine correlations between MYOZ expression and fiber type mean percent occupancies. Results: The main aim of this project was to determine whether expression of the three calsarcin genes, MYOZ1, 2, and 3, differs between subjects with RR, RX and XX genotypes for the ACTN3 gene, as well as between sagittal and vertical classes of malocclusion, asymmetries and TMD. Differences were found for MYOZ3 expression where relative quantities in males, but not females, decreased progressively from the ACTN3 RR, to RX, and XX genotypes. Among subjects with the RX genotype, expression differed significantly between males and females by an unpaired t-test. A statistically significant difference was detected between MYOZ2 and Class II, Class III malocclusions (p=0.05). Sagittal differences were compared further by ANOVA analyses with a statistically significant difference detected for MYOZ3 with a probability of 0.02. Correlation analyses comparing fiber type mean % occupancy with calsarcin gene expression revealed a significant positive relationship between MYOZ2 and type I (slow-twitch) fibers. Correspondingly, a significant correlation of MYOZ2 expression with type IIA and IIX (fast-twitch) fibers was negative. Conclusions: The greatest relative quantity of RNA for the three calsarcin genes was found in MYOZ3, suggesting more calsarcin-3 may be needed in masticatory muscle structure and function than other calsarcin isoforms. Alternatively, high expression of MYOZ3 in the masseter samples may indicate that there are relatively greater amounts of that isoform in cranial muscle than in the limb skeletal muscle standard used in these studies. Also, relative quantities of MYOZ3 expression in males decreased progressively from the ACTN3 RR, to RX, and XX genotypes. While this data may suggest that the ACTN3 R577X polymorphism may affect MYOZ3 expression in males of the malocclusion patient population, an increased sample of male subjects would be needed to determine if this trend has true significance. Expression of MYOZ2 (calsarcin-1) was strongly correlated with slow fiber-type occupancy in masseter muscle of our patient population. The muscle-specific expression of each calsarcin may lend to the understanding of this result. MYOZ2 is the only isoform found in both cardiac muscle and slow-twitch skeletal muscle, while MYOZ1 and MYOZ3 are both found in skeletal muscle with a predilection towards fast-twitch skeletal muscle (Frey et al., 2004).
Temple University--Theses
Lavery, William Lindsay. "Investigation of changes in gene expression during ageing of the liver". Thesis, University of Sunderland, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.288934.
Pełny tekst źródłaShen, Shixue. "Differential gene expression in innate immunity between commercial broilers and layers". [College Station, Tex. : Texas A&M University, 2006. http://hdl.handle.net/1969.1/ETD-TAMU-1848.
Pełny tekst źródłaMutlu, Pelin. "Differential Gene Expression Analysis In Drug Resistant Multiple Myeloma Cell Lines". Phd thesis, METU, 2009. http://etd.lib.metu.edu.tr/upload/3/12610970/index.pdf.
Pełny tekst źródłaIlling, Nicola. "The control of differential gene expression during sporulation in Bacillus subtilis". Thesis, University of Oxford, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.276812.
Pełny tekst źródłaMoran, Mary Teresa. "Gaucher's disease : differential gene expression in the understanding of its pathogenesis". Thesis, University of Cambridge, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.621720.
Pełny tekst źródłaNdimande, Gordon Sandile. "Comparative analysis of differential gene expression in the culms of sorghum". Thesis, Stellenbosch : University of Stellenbosch, 2007. http://hdl.handle.net/10019.1/2903.
Pełny tekst źródłaDespite numerous attempts involving a variety of target genes, the identity of the key regulatory genes of sucrose metabolism in sugarcane is still illusive. To date, genomic research into sucrose accumulation in sugarcane has focused on genes that are expressed in association with stalk development/maturation, with the aim of identifying key regulatory steps in sucrose metabolism. The identification of possible controlling points, however, is complicated by the polyploid nature of sugarcane. Although these studies have yielded extensive annotated gene lists and correlative data, the identity of key regulatory genes remains elusive. A close relative of sugarcane, Sorghum bicolor, is diploid, has a small genome size and accumulates sucrose in the stalk parenchyma. The main aim of the work presented in this thesis was to use S. bicolor as a model to identify genes that are differentially expressed during sucrose accumulation in the stalk of low and high sucrose genotypes. In the first part of the study, a macroarray protocol for identification of differentially expressed genes during sorghum development was established. Firstly, the macroarray sensitivity of probe-target hybridisation was optimised with increasing amounts of target DNA i.e. 0.005-0.075 pmol. The hybridisation signal intensity increased as expected with increasing amounts of probe until the hybridisation signals reached maximum levels at 0.05 pmol. As a result, to ensure quantitative cDNA detection, probes were arrayed at 0.05 pmol when 1 μg target cDNA was used. Secondly, intra-array and inter-array membrane reproducibility was found to be high. In addition, the protocol was able to detect species of mRNA at the lowest detection limit tested (0.06%) and permits the detection of an eight-fold variation in transcript levels. The conclusion was therefore that the protocol was reproducible, robust and can reliably detect changes in mRNA levels. In the second part of the study, sugar accumulation levels in the immature and maturing internodal tissues of sorghum GH1 and SH2 genotypes were compared during the boot and softdough stages. Sugars (i.e. fructose, glucose and sucrose) accumulated differently in the immature and maturing internodes in both sorghum genotypes during the boot and softdough stages, with sucrose being the dominant sugar in both stages. Based on these differences in sugar accumulation patterns, immature and maturing internodal tissues of sorghum genotypes were compared for differentially expressed genes. A number of genes were found to be significantly differentially expressed during both stages. In order to validate the reliability of the macroarray analysis, fourteen genes were arbitrarily selected for semi-quantitative RT-PCR. Seven genes (50%) revealed a similar pattern of transcript expression, confirming the macroarray results. The other seven genes, however, showed a different expression trend compared with the macroarrays. In this study, ESTs from rice and sugarcane were used for probing sorghum. The probability of cross-hybridisation between the probes and various isoforms of the homologous sorghum sequences is thus high, potentially leading to the identification of false positives. In addition, variation in expression patterns could have been introduced by technical and biological variation. Lastly, to verify that changes in the levels of a transcript are also reflected in changes in enzyme activity, seven candidates were tested for enzyme activity. Only three i.e. soluble acid invertase (SAI), sucrose synthase (SuSy) and alcohol dehydrogenase (ADH), out of these seven genes showed enzyme activity levels reflective of the relative transcript expression. We concluded that changes in transcript levels may or may not immediately lead to similar changes in enzyme activity. In addition, enzyme activity may be controlled at transcriptional and at posttranscriptional levels. In conclusion, sugar accumulation in low (GH1) and high (SH2) sucrose sorghum genotypes is influenced by differences in gene expression. In addition, the power of macroarrays and confirmation with semi-quantitative RT-PCR for identification of differentially expressed genes in sorghum genotypes was demonstrated. Moreover, the transcript and enzyme activity patterns of SAI, SuSy and ADH genes showed expression patterns similar to those of sugarcane during sucrose accumulation. Therefore, using sorghum as a model promises to enhance and refine our understanding of sucrose accumulation in sugarcane.
Choi, Hye Won. "Differential regulation of PTH-induced primary response gene expression in osteoblasts". Diss., Restricted to subscribing institutions, 2009. http://proquest.umi.com/pqdweb?did=1905636821&sid=1&Fmt=2&clientId=1564&RQT=309&VName=PQD.
Pełny tekst źródłaWebb, Steven Anthony Rochford. "Evaluation of differential gene expression in Neisseria meningitidis using a Green Fluorescent Protein reporter sytem". Thesis, Imperial College London, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.246674.
Pełny tekst źródłaGlaus, Peter. "Bayesian methods for gene expression analysis from high-throughput sequencing data". Thesis, University of Manchester, 2014. https://www.research.manchester.ac.uk/portal/en/theses/bayesian-methods-for-gene-expression-analysis-from-highthroughput-sequencing-data(cf9680e0-a3f2-4090-8535-a39f3ef50cc4).html.
Pełny tekst źródłaCheng, Hai-Ying Mary. "Differential gene expression in presentation versus drug-resistant relapse AML, in search of drug resistance genes by the differential display approach". Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape7/PQDD_0021/MQ45860.pdf.
Pełny tekst źródłaGower, Adam C. "Discovering biological connections between experimental conditions based on common patterns of differential gene expression". Thesis, Boston University, 2012. https://hdl.handle.net/2144/32019.
Pełny tekst źródłaPLEASE NOTE: Boston University Libraries did not receive an Authorization To Manage form for this thesis or dissertation. It is therefore not openly accessible, though it may be available by request. If you are the author or principal advisor of this work and would like to request open access for it, please contact us at open-help@bu.edu. Thank you.
Similarities between patterns of differential gene expression can be used to establish connections between the experimental and biological conditions that give rise to them. The growing volume of gene expression data in repositories such as NCBI's Gene Expression Omnibus (GEO) presents an opportunity to identify such similarities on a large scale across a diverse collection of datasets. In this work, I have developed a pattern-based approach, named openSESAME, to identify datasets enriched in samples displaying coordinate differential expression of a query signature. Importantly, openSESAME performs this search without knowledge of the experimental groups in the datasets being searched, which allows it to identify perturbations of gene expression due to attributes that may not have been recorded. First, I demonstrated the utility of openSESAME using two gene expression signatures to query a set of more than 75,000 human expression profiles obtained from GEO. A query using a signature of estradiol treatment identified experiments in which estrogen signaling was perturbed and also discriminated between estrogen receptor-positive and -negative breast cancers. A second query using a signature of silencing of the transcription factor p63 (a key regulator of epidermal differentiation) identified datasets related to stratified squamous epithelia or epidermal diseases such as melanoma. Next, to improve the utility of openSESAME, I expanded the collection of profiles to include samples from mouse and rat, and automatically translated expression signatures for cross-species queries. Furthermore, I processed the sample annotation associated with these samples in GEO, extracting informative words and phrases and continuous (e.g., age) and categorical (e.g., disease state) variables. I have also recorded sample-specific dates and quality metrics to assess whether batch effects or outliers are affecting individual query results. Finally, I used openSESAME to query this repository with over 800 gene expression signatures from the Broad Institute's Molecular Signatures Database (MSigDB). I then used the scores of the association of each signature with each sample in the repository to build a network of the relatedness of these signatures to each other. This "constellation" of signatures can be used to determine the relationship of a query signature to other biological and experimental perturbations.
2031-01-02
Mapiye, Darlington S. "Normalization and statistical methods for crossplatform expression array analysis". University of the Western Cape, 2012. http://hdl.handle.net/11394/4586.
Pełny tekst źródłaA large volume of gene expression data exists in public repositories like the NCBI’s Gene Expression Omnibus (GEO) and the EBI’s ArrayExpress and a significant opportunity to re-use data in various combinations for novel in-silico analyses that would otherwise be too costly to perform or for which the equivalent sample numbers would be difficult to collects exists. For example, combining and re-analysing large numbers of data sets from the same cancer type would increase statistical power, while the effects of individual study-specific variability is weakened, which would result in more reliable gene expression signatures. Similarly, as the number of normal control samples associated with various cancer datasets are often limiting, datasets can be combined to establish a reliable baseline for accurate differential expression analysis. However, combining different microarray studies is hampered by the fact that different studies use different analysis techniques, microarray platforms and experimental protocols. We have developed and optimised a method which transforms gene expression measurements from continuous to discrete data points by grouping similarly expressed genes into quantiles on a per-sample basis. After cross mapping each probe on each chip to the gene it represents, thereby enabling us to integrate experiments based on genes they have in common across different platforms. We optimised the quantile discretization method on previously published prostate cancer datasets produced on two different array technologies and then applied it to a larger breast cancer dataset of 411 samples from 8 microarray platforms. Statistical analysis of the breast cancer datasets identified 1371 differentially expressed genes. Cluster, gene set enrichment and pathway analysis identified functional groups that were previously described in breast cancer and we also identified a novel module of genes encoding ribosomal proteins that have not been previously reported, but whose overall functions have been implicated in cancer development and progression. The former indicates that our integration method does not destroy the statistical signal in the original data, while the latter is strong evidence that the increased sample size increases the chances of finding novel gene expression signatures. Such signatures are also robust to inter-population variation, and show promise for translational applications like tumour grading, disease subtype classification, informing treatment selection and molecular prognostics.
Voelker, Courtney Christine Joan. "Differential gene expression of cortical layer V pyramidal neuron subpopulations during development". Thesis, University of Oxford, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.436930.
Pełny tekst źródłaLewis, Marie. "Cell survival, biofilm formation and differential gene expression of two opportunistic pathogens". Thesis, University of Exeter, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.410813.
Pełny tekst źródłaKapushesky, Misha. "Construction and analysis of a multi-species atlas of differential gene expression". Thesis, University of Cambridge, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.608589.
Pełny tekst źródłaTchakounte, Wakem Seguy. "A Comparison of Methods Taking into Account Asymmetry when Evaluating Differential Expression in Gene Expression Experiments". Thesis, North Dakota State University, 2018. https://hdl.handle.net/10365/28874.
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