Dissertations / Theses on the topic 'Phenotype'
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Moses, Lorraine. "Phenotypic factors influencing Mycobacterium tuberculosis phenotype." Thesis, Stellenbosch : Stellenbosch University, 2002. http://hdl.handle.net/10019.1/52997.
Full textSailer, Zachary. "Predicting Phenotypes in Sparsely Sampled Genotype-Phenotype Maps." Thesis, University of Oregon, 2019. http://hdl.handle.net/1794/24231.
Full text2020-01-11
Arbon, Jed. "Phenotype-genotype correlation between the Hippo pathway and 3D craniofacial phenotypes." Thesis, University of Iowa, 2016. https://ir.uiowa.edu/etd/3042.
Full textHabib, Farhat Abbas. "Genotype-phenotype correlation using phylogenetic trees." Columbus, Ohio : Ohio State University, 2007. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1187297400.
Full textBloomfield, Kelly Louise, and n/a. "Investigation of the Role of Thioredoxin in the Invasive Phenotype and its Interaction with the Transcription Factor Sp1." Griffith University. School of Biomolecular and Biomedical Science, 2003. http://www4.gu.edu.au:8080/adt-root/public/adt-QGU20031021.120018.
Full textBloomfield, Kelly Louise. "Investigation of the Role of Thioredoxin in the Invasive Phenotype and its Interaction with the Transcription Factor Sp1." Thesis, Griffith University, 2003. http://hdl.handle.net/10072/366170.
Full textThesis (PhD Doctorate)
Doctor of Philosophy (PhD)
School of Biomolecular and Biomedical Sciences
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Ried, Janina S. "Phenotype set enrichment analysis." Diss., Ludwig-Maximilians-Universität München, 2013. http://nbn-resolving.de/urn:nbn:de:bvb:19-158079.
Full textAlsbou, Mohammed. "Dissecting phenotype-genoype relationships." Thesis, University of Liverpool, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.443925.
Full textARDISSONE, ANNA. "Mitochondrial diseases related to mtDNA in childhood: genotype-phenotype correlation and characterization of novel phenotypes." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2020. http://hdl.handle.net/10281/262917.
Full textMitochondrial diseases (MD) are a clinically heterogeneous group of disorders that arise as a result of dysfunction of the mitochondrial respiratory chain (RC) and oxidative phosphorylation (OXPHOS). Mitochondrial functions are under the control of two different genomes: mitochondrial DNA (mtDNA) and nuclear genome (nDNA). Childhood phenotypes are often associated with nDNA mutations; in recent years, new-generation sequencing technologies (Next Generation Sequencing-NGS) have identified novel causative genes; in collaboration with other centers we contributed to the definition of phenotype associated with the new identified disease genes. The application of this technique has also been extended to the study of mtDNA: even if more than 100 mutations and deletions in mtDNA have been described in association with an extremely heterogeneous spectrum of clinical presentations, only a few of them are associated with well-defined clinical syndromes in childhood. We performed a systematic evaluation of clinical, instrumental, metabolic and biochemical data of a large cohort of patients affected by the most common MD in childhood: Leigh syndrome. We analyzed in this population, genotype-phenotype correlation in nDNA and mtDNA gene associated cases in order to identify diagnostic clues for mtDNA related Leigh syndrome. In genetically unresolved cases and various phenotypes (Leigh syndrome, leukodystropy..), we performed mtDNA screening using next-generation sequencing (NGS) technologies in order to assess, with high accuracy, point mutations and single or multiple large deletions, both in homoplasmic or heteroplasmic state. We identified both novel and known mutations associated to unexpected phenotype (i.e. CO3 gene). Our data better define and expand the phenotypic spectrum of mtDNA-MD in childhood.
Gale, Christopher Robert Keith. "Newborn feeding and infant phenotype." Thesis, Imperial College London, 2013. http://hdl.handle.net/10044/1/39361.
Full textClark, Corinna C. A. "Understanding the phenotype of aggressiveness." Thesis, University of Edinburgh, 2007. http://hdl.handle.net/1842/27801.
Full textPontius, Sarah E. "Genotype-Phenotype: Investigations in Typology." Cincinnati, Ohio : University of Cincinnati, 2007. http://www.ohiolink.edu/etd/view.cgi?acc%5Fnum=ucin1179414436.
Full textTitle from electronic theses title page (viewed July 16, 2007). Includes abstract. Keywords: architecture; typology; therapeutic; riding stable Includes bibliographic references.
Bing, Xinyang (David). "Transvection is a plastic phenotype." Thesis, Laurentian University of Sudbury, 2013. https://zone.biblio.laurentian.ca/dspace/handle/10219/2120.
Full textGordon-Smith, Katherine Mary. "Neuropsychiatric phenotype in Darier's Disease." Thesis, Cardiff University, 2008. http://orca.cf.ac.uk/55734/.
Full textCheong, Pak Leng. "Genotype-Phenotype Correlations in Porphyria." Thesis, The University of Sydney, 2015. http://hdl.handle.net/2123/13647.
Full textBabbi, Giulia <1991>. "The biological complexity of the genotype-phenotype relation: from genes and proteins to phenotypes and diseases." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2019. http://amsdottorato.unibo.it/9042/1/Babbi_Giulia_tesi.pdf.
Full textRied, Janina S. [Verfasser], and H. Erich [Akademischer Betreuer] Wichmann. "Phenotype set enrichment analysis : genome wide analysis of multiple phenotypes / Janina S. Ried. Betreuer: H.-Erich Wichmann." München : Universitätsbibliothek der Ludwig-Maximilians-Universität, 2013. http://d-nb.info/1036836894/34.
Full textRamon, Gurrea Elies. "Kernel approaches for complex phenotype prediction." Doctoral thesis, Universitat Autònoma de Barcelona, 2020. http://hdl.handle.net/10803/671296.
Full textLa relación entre fenotipo e información genotípica es considerablemente intrincada y compleja. Los métodos de aprendizaje automático (ML) se han utilizado con éxito para la predicción de fenotipos en una gran variedad de problemas dentro de la genética y la genómica. Sin embargo, los datos biológicos suelen estar estructurados y pertenecer a tipos de datos "no estándar", lo que puede representar un desafío para la mayoría de los métodos de ML. Entre ellos, los métodos de kernel permiten un enfoque muy versátil para manejar diferentes tipos de datos y problemas mediante una familia de funciones llamadas de kernel. El objetivo principal de esta tesis doctoral es el desarrollo y evaluación de enfoques de kernel específicos para la predicción fenotípica, centrándose en problemas biológicos con tipos de datos o diseños experimentales estructurados. En la primera parte, usamos secuencias de proteínas mutadas del VIH (proteasa, transcriptasa inversa e integrasa) para predecir la resistencia a antiretrovirales. Proponemos dos funciones de kernel categóricas (Overlap y Jaccard) que tienen en cuenta las particularidades de los datos de VIH, como las mezclas de alelos. Los kernels propuestos se combinan con máquinas de vector soporte (SVM) y se comparan con dos funciones de kernel estándar (Linear y RBF) y dos métodos que no son de kernel: bosques aleatorios (RF) y un tipo de red neuronal, el perceptrón multicapa. También incluimos en los kernels la importancia relativa de cada posición de la proteína con respecto a la resistencia. Tener en cuenta tanto la naturaleza categórica de los datos como la presencia de mezclas obtenemos sistemáticamente mejores predicciones. El efecto de la ponderación es mayor en los inhibidores de la integrasa y la transcriptasa inversa, lo que puede estar relacionado con diferencias en los patrones mutacionales de las tres enzimas virales. En la segunda parte, ampliamos el estudio anterior para considerar que las posiciones de las proteínas pueden no ser independientes. Las secuencias mutadas se representan como grafos, ponderándose las aristas por la distancia euclidiana entre residuos obtenida por cristalografía de rayos X. A continuación, se calcula un kernel para grafos (el exponential random walk kernel) que integra los kernels Overlap y Jaccard. A pesar de las ventajas potenciales de este enfoque, no observamos una mejora en la capacidad predictiva. En la tercera parte, proponemos un kernel framework para unificar los análisis supervisados y no supervisados del microbioma. Para ello, usamos una misma matriz de kernel para predecir fenotipos usando SVM y visualización a través de análisis de componentes principales con kernels (kPCA). Definimos dos kernels para datos composicionales (Aitchison-RBF y compositional linear) y discutimos la transformación de medidas de beta-diversidad en kernels. El kernel lineal composicional también permite la recuperación de importancias de taxones (firmas microbianas) del modelo SVM. Para datos con estructura espacial y temporal usamos Multiple Kernel Learning y kernels para series temporales, respectivamente. Ilustramos el kernel framework con tres conjuntos de datos: datos de suelos, datos humanos con un componente espacial y, un conjunto de datos longitudinales inéditos sobre producción porcina. Todos los análisis incluyen una comparación con los informes originales (en los dos primeros casos), así como un contraste con los resultados de RF. El kernel framework no solo permite una visión holística de los datos, sino que también da buenos resultados en cada área de aprendizaje. En análisis no supervisados, los principales patrones detectados en los estudios originales se conservan en kPCA. En análisis supervisados, la SVM tiene un rendimiento mayor (o equivalente) a los RF, mientras que las firmas microbianas son coherentes con los estudios originales y la literatura previa.
The relationship between phenotype and genotypic information is considerably intricate and complex. Machine Learning (ML) methods have been successfully used for phenotype prediction in a great range of problems within genetics and genomics. However, biological data is usually structured and belongs to & 'nonstandard' data types, which can pose a challenge to most ML methods. Among them, kernel methods bring along a very versatile approach to handle different types of data and problems through a family of functions called kernels. The main goal of this PhD thesis is the development and evaluation of specific kernel approaches for phenotypic prediction, focusing on biological problems with structured data types or study designs. In the first part, we predict drug resistance from HIV-mutated protein sequences (protease, reverse transcriptase and integrase). We propose two categorical kernel functions (Overlap and Jaccard) that take into account HIV data particularities, such as allele mixtures. The proposed kernels are coupled with Support Vector Machines (SVM) and compared against two well-known standard kernel functions (Linear and RBF) and two nonkernel methods: Random Forests (RF) and the Multilayer Perceptron neural network. We also include a relative weight into the aforementioned kernels, representing the importance of each protein residue regarding drug resistance. Taking into account both the categorical nature of data and the presence of mixtures consistently delivers better predictions. The weighting effect is higher in reverse transcriptase and integrase inhibitors, which may be related to the different mutational patterns in the viral enzymes regarding drug resistance. In the second part, we extend the previous study to consider the fact that protein positions are not independent. Mutated sequences are modeled as graphs, with edges weighted by the Euclidean distance between residues, obtained from crystal three-dimensional structures. A kernel for graphs (the exponential random walk kernel) that integrates the previous Overlap and Jaccard kernels is then computed. Despite the potential advantages of this kernel for graphs, an improvement on predictive ability as compared to the kernels of the first study is not observed. In the third part, we propose a kernel framework to unify unsupervised and supervised microbiome analyses. To do so, we use the same kernel matrix to perform phenotype prediction via SVMs and visualization via kernel Principal Components Analysis (kPCA). We define two kernels for compositional data (Aitchison-RBF and compositional linear) and discuss the transformation of beta-diversity measures into kernels. The compositional linear kernel also allows the retrieval of taxa importances (microbial signatures) from the SVM model. Spatial and time-structured datasets are handled with Multiple Kernel Learning and kernels for time series, respectively. We illustrate the kernel framework with three datasets: a single point soil dataset, a human dataset with a spatial component, and a previously unpublished longitudinal dataset concerning pig production. Analyses across the three case studies include a comparison with the original reports (for the two former datasets), as well as contrast with results from RF. The kernel framework not only allows a holistic view of data but also gives good results in each learning area. In unsupervised analyses, the main patterns detected in the original reports are conserved in kPCA. In supervised analyses SVM has better (or, in some cases, equivalent) performance than RF, while microbial signatures are consistent with the original studies and previous literature.
Petsch, Katherine Anne. "Characterisation of the arabidopsis broomhead phenotype /." [St. Lucia, Qld.], 2005. http://www.library.uq.edu.au/pdfserve.php?image=thesisabs/absthe19189.pdf.
Full textTaylor, Lisa. "Behavioural phenotype of Smith-Magenis syndrome." Thesis, University of Birmingham, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.435388.
Full textBurke, Georgina. "Genotype - phenotype correlations in congenital myasthenia." Thesis, University of Oxford, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.437178.
Full textAbhishek, Abhishek. "Chondrocalcinosis : risk factors and radiographic phenotype." Thesis, University of Nottingham, 2012. http://eprints.nottingham.ac.uk/12926/.
Full textBeck, Timothy Joseph. "A phenotype ontology for fission yeast." Thesis, University of Sussex, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.488618.
Full textBaldwin, C. V. F. "Regulation of phenotype in Pseudomonas tolaasii." Thesis, University of Cambridge, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.596304.
Full textAhmed, S. "The clinical phenotype of early dementia." Thesis, University of Cambridge, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.595383.
Full textJäger, Fiona Isabel [Verfasser], and Bodo [Akademischer Betreuer] Grimbacher. "Immunological phenotype of LRBA-deficient mice." Freiburg : Universität, 2019. http://d-nb.info/1186794461/34.
Full textGhasimi, Soma. "Genotype-phenotype studies in brain tumors." Doctoral thesis, Umeå universitet, Onkologi, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-83185.
Full textCancer research foundation in northern Sweden and Lions cancer research foundation at Umeå university
McGoldrick, Adrian. "Attenuation phenotype of poliovirus type 1." Thesis, University of Reading, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.295307.
Full textRodie, Martina Elizabeth. "Characterisation of the androgen dependent phenotype." Thesis, University of Glasgow, 2017. http://theses.gla.ac.uk/8540/.
Full textDe, Souza Jennifer Charlotte. "The psychiatric phenotype in Huntington's disease." Thesis, University of Birmingham, 2015. http://etheses.bham.ac.uk//id/eprint/5875/.
Full textHabib, Farhat. "Genotype-phenotype correlation using phylogenetic trees." The Ohio State University, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=osu1187297400.
Full textJordan, Natasha Patricia. "Genotype-phenotype relations in lupus nephritis." Thesis, King's College London (University of London), 2014. http://kclpure.kcl.ac.uk/portal/en/theses/genotypephenotype-relations-in-lupus-nephritis(645d8e22-23b7-40d5-8c8d-23efeabf5d56).html.
Full textDingle, Kamaludin. "Probabilistic bias in genotype-phenotype maps." Thesis, University of Oxford, 2014. http://ora.ox.ac.uk/objects/uuid:eba8801e-182e-42f5-aa0a-d3d914fd7923.
Full textLow, Andrew John. "Using genotypic and phenotypic methods to determine the HIV co-receptor phenotype in the clinical setting." Thesis, University of British Columbia, 2007. http://hdl.handle.net/2429/226.
Full textDing, Zhihao. "The genetics of cellular phenotypes." Thesis, University of Cambridge, 2015. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.708712.
Full textCalleja, Yagüe María Isabel. "Neuronal phenotype characterization of FAIM-KO mice." Doctoral thesis, Universitat Autònoma de Barcelona, 2019. http://hdl.handle.net/10803/669392.
Full textFas apoptotic inhibitory molecule 1 (FAIM1) gene is highly conserved in the evolution and was firstly characterized in B cells in 1999. FAIM1 codifies for at least four isoforms, among which FAIM-L and FAIM-S are the most relevant. FAIM-L is formed by alternative splicing, is exclusively expressed in neurons and contains twenty-two amino acids more than the first isoform characterized in B cells, FAIM-S. The first described role of FAIM1 was this protective effect against death-receptor mediated cell death. FAIM-S and FAIM-L exert this function in different cells, and FAIM-L is the only FAIM1 isoform that protects neurons against induced apoptosis. Recently, a protective role of FAIM1 in cellular stress-induced cell death has been reported. FAIM1 have been also implicated in non-apoptotic functions. FAIM-S participates in different non-apoptotic functions in the immune system, in glucose and lipid metabolism, in protein aggregation and in neurite outgrowth. Otherwise, FAIM-L acts as a regulator in synaptic transmission, axonal degeneration and synaptic plasticity process of long-term depression. Besides, FAIM1 isoforms have relevant roles in different diseases. In that sense, FAIM-S is deregulated in multiple myeloma and obesity and FAIM-L is downregulated in Alzheimer’s disease. Although some FAIM1 isoforms functions have been reported in nervous system, many questions about their actions in CNS are still a high exciting mystery. Therefore, we decided to characterize the neuronal phenotype of FAIM-KO mice to unravel FAIM1 functions in brain. Surprisingly, we observed age-dependent sensory-induced seizures in FAIM-KO mice. Owing to that finding, the work was focused to unravel mechanisms related with seizure susceptibility in FAIM-KO mice. FAIM-KO mice with seizure showed typical hippocampal cellular and molecular alterations reported in epilepsy models such ectopic neuropeptide Y expression, increase neurogenesis and increase c-fos expression in hippocampus. However, these effects have not been observed in non-convulsive FAIM-KO mice. Although, neuroinflammation and cell death were not apparent in FAIM-KO mice, these animals exhibit a decrease in glial density in hippocampus and alterations in parvalbumin- and calretinin-containing interneuron populations. These mice also exhibited slightly changes in the expression of synaptic proteins SNAP25 and vGLUT1, deregulation in mRNA levels of Fas and XIAP, and alteration in primary dendrites of granule cells in hippocampus. Interestingly, FAIM-KO mice were hyperactive, had impairment in cognitive tasks and in nest construction and exhibited an increase in social interactions. These results point to new exciting roles of FAIM1 in CNS. However, the use in this work of FAIM-KO mice derived of mixed background makes the replication of these experiments in other genetic background necessary for ensuring a role of FAIM1 in seizure susceptibility.
Khasawneh, Ramada Rateb. "Msx1 modulates the Pax9-null cardiovascular phenotype." Thesis, University of Newcastle upon Tyne, 2016. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.725264.
Full textSouthward, Katie Hannah. "Genotype, phenotype and outcomes in colorectal cancer." Thesis, University of Leeds, 2016. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.713695.
Full textKhasawneh, Ramada Rateb Abdel Karim. "Msx1 modulates the Pax9-null cardiovascular phenotype." Thesis, University of Newcastle upon Tyne, 2017. http://hdl.handle.net/10443/3668.
Full textBrais, Bernard. "Oculopharyngeal muscular dystrophy : from phenotype to genotype." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape11/PQDD_0002/NQ44369.pdf.
Full textMasterman, Thomas. "Heritable modulators of the multiple sclerosis phenotype /." Stockholm, 2002. http://diss.kib.ki.se/2002/91-628-5383-x/.
Full textDebiparshad, Kevin. "Musculoskeletal phenotype of Egr-1 deficient mice." Thesis, McGill University, 2010. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=86749.
Full textWild-type (+/+) C57Bl/6 or Egr-1-deficient (−/−) mice were sacrificed at the same age interval (8- to 9-months). Standard histological preparation and staining with Safranin-O/Fast Green were done. Also immuncohistochemistry was performed using anti-bodies to type X collagen, cleavage products of both type II collagen and aggrecan. Imaging of mice was with plain radiographs, bone mineral density measurements and microCT analysis.
Results revealed that these mice have differences including abnormal bone structure and density, structural and possibly compositional differences in articular cartilage and structural and biochemical changes in IVDs. This points to the importance of Egr-1 in the maintenance of normal bone, IVD and articular cartilage and makes it a possible target for initiating pathological conditions of these tissues.
La protéine de croissance EGR-1 (Early Growth Response protein-1, en anglais) est un facteur de transcription qui est induit par la tension ou la blessure, les facteurs mitogènes, et les facteurs de différenciation. EGR-1 est ainsi régulé par divers cytokines, facteurs de croissance, par les conditions ischémique, ainsi que la tension et les blessures mécaniques. Ces régulateurs ont été reliés au développement ainsi que la dégradation du système squeletto-musculaire, particulièrement le cartilage articulaire, les disques intervertébraux (DIV) et l'os. De plus, il a été démontré que EGR-1 peut réguler l'expression des collagènes et d'enzymes contribuant à la matrice extracellulaire. Le polymorphisme de séquences d'ADN pour les des sites d'attachements d'EGR-1 a démontré être associé avec la dégradation de disques intervertébraux et l'ostéoporose. L'objectif de cette étude était de déterminer l'effet d'une expression réduite d'EGR-1 sur les phénotypes du cartilage articulaire, les DIV, et l'os.
Les souris C57Bl/6 de phénotype sauvage (+/+) ou ceux avec une expression réduite d'EGR-1 (−/−) ont été sacrifiées au même intervalle d'âge (8 à 9 mois). La préparation histologique standard et la coloration avec Safranin-O/Fast Green a été fait. Aussi l'immunohistochimie a été exécuté avec des anticorps pour le collagène de type X, et les produits de clivage du collagène de type II ainsi que les aggrécanes. L'imagerie de souris a été faite avec les radiographies simples, les mesures de densité minéraux de l'os, et avec l'analyse de micro-tomodensitomètre.
Les résultats ont révélé que ces souris ont des différences incluant la structure et densité d'os anormaux, les différences structurelles et possiblement compositionnelles dans le cartilage articulaire, et les changements structurels et biochimiques dans les DIV. Ceci indique à l'importance d'EGR-1 dans l'entretien d'os normal, des DIV et le cartilage articulaire, et le rend une cible possible pour initier les conditions pathologiques de ces tissus.
Miller, Gabriel A. "Immunity, nutrition and phenotype in locust ecology." Thesis, University of Oxford, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.497052.
Full textLu, Song, and 鲁嵩. "Phenotype analysis of Pdss2 conditional knockout mouse." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2010. http://hub.hku.hk/bib/B45552381.
Full textWu, Chuang. "Phenotype Inference from Genotype in RNA Viruses." Research Showcase @ CMU, 2014. http://repository.cmu.edu/dissertations/457.
Full textIsmail, Endom. "Gene expression contributing to the metastatic phenotype." Thesis, University of Glasgow, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.402743.
Full textO'Brien, Kirtsy K. "Genotype - phenotype relationships in late onset dementia." Thesis, University of Newcastle Upon Tyne, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.402161.
Full textHutchings, A. D. "The measurement of acetylator phenotype in man." Thesis, University of South Wales, 1987. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.376091.
Full textDewberry, Rachael Marie. "The genetic control of endothelial cell phenotype." Thesis, University of Sheffield, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.420791.
Full textEmmett, C. "Astroglial phenotype in vivo and in vitro." Thesis, University College London (University of London), 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.380695.
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