Relevant bibliographies by topics / Genomic DNA detection / Dissertations / Theses
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Dissertations / Theses on the topic 'Genomic DNA detection'

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Published: 4 June 2021
Last updated: 14 February 2022

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1

Miller, James Keith. "Exon and intron detection in human genomic DNA." Online access for everyone, 2005. http://www.dissertations.wsu.edu/Dissertations/Spring2005/j%5Fmiller%5F030705.pdf.

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2

Maw, Khin Lay. "Development of a Novel DNA Microchip for Pathogen Detection." Digital Archive @ GSU, 2010. http://digitalarchive.gsu.edu/chemistry_theses/34.

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Although DNA microarray can detect multiple DNA samples simultaneously, current detection techniques involve PCR and other traditional procedures. In this study, a sensitive, specific and rapid detection method, which eliminates PCR and other lengthy processes, for pathogenic DNA is presented. This technology is based on the hybridization of target DNA to the immobilized probe, extension of probe DNAs using the target-DNA as a template and signal generation by streptavidin-horseradish peroxidase and substrate. This method is highly specific and sensitive, allowing single-nucleotide-base mismatches discrimination and the detection at femtomole level. The experiments are designed to achieve short hybridization time. Therefore, satisfactory signal can be detected within minutes, allowing the rapid detection of multiple pathogenic DNA. Most importantly, the E. coli genomic DNA can be detected using this technology. In conclusion, this detection method is useful for applications including on-site pathogenic disease detection, crime scene investigation, and pathogen inspection in the environment.
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3

Feng, Yuanjian. "Detection and Characterization of Multilevel Genomic Patterns." Diss., Virginia Tech, 2010. http://hdl.handle.net/10919/38577.

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DNA microarray has become a powerful tool in genetics, molecular biology, and biomedical research. DNA microarray can be used for measuring the genotypes, structural changes, and gene expressions of human genomes. Detection and characterization of multilevel, high-throughput microarray genomic data pose new challenges to statistical pattern recognition and machine learning research. In this dissertation, we propose novel computational methods for analyzing DNA copy number changes and learning the trees of phenotypes using DNA microarray data. DNA copy number change is an important form of structural variations in human genomes. The copy number signals measured by high-density DNA microarrays usually have low signal-to-noise ratios and complex patterns due to inhomogeneous composition of tissue samples. We propose a robust detection method for extracting copy number changes in a single signal profile and consensus copy number changes in the signal profiles of a population. We adapt a solution-path algorithm to efficiently solve the optimization problems associated with the proposed method. We tested the proposed method on both simulation and real CGH and SNP microarray datasets, and observed competitively improved performance as compared to several widely-adopted copy number change detection methods. We also propose a chromosome instability measure to summarize the extracted copy number changes for assessing chromosomal instabilities of tumor genomes. The proposed measure demonstrates distinct patterns between different subtypes of ovarian serous carcinomas and normal samples. Among active research on complex human diseases using genomic data, little effort and progress have been made in discovering the relational structural information embedded in the molecular data. We propose two stability analysis based methods to learn stable and highly resolved trees of phenotypes using microarray gene expression data of heterogeneous diseases. In the first method, we use a hierarchical, divisive visualization approach to explore the tree of phenotypes and a leave-one-out cross validation to select stable tree structures. In the second method, we propose a node bandwidth constraint to construct stable trees that can balance the descriptive power and reproducibility of tree structures. Using a top-down merging procedure, we modify the binary tree structures learned by hierarchical group clustering methods to achieve a given node bandwidth. We use a bootstrap based stability analysis to select stable tree structures under different node bandwidth constraints. The experimental results on two microarray gene expression datasets of human diseases show that the proposed methods can discover stable trees of phenotypes that reveal the relationships between multiple diseases with biological plausibility.
Ph. D.
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4

Hersh, Megan N. "VISUALIZING GENOMIC INSTABILITY: IN SITU DETECTION AND QUANTIFICATION OF MUTATION IN MICE." University of Cincinnati / OhioLINK, 2001. http://rave.ohiolink.edu/etdc/view?acc_num=ucin991312483.

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5

Beiko, Robert G. "Evolutionary computing strategies for the detection of conserved patterns in genomic DNA." Thesis, University of Ottawa (Canada), 2003. http://hdl.handle.net/10393/29009.

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The detection of regulatory sequences in DNA is a challenging problem, especially when considered in the context of whole genomes. The degree of sequence conservation of regulatory protein binding sites is often weak, and the sites are obscured by surrounding intergenic sequence. Since structural interactions are vital for protein-DNA interactions, structural representations of regulatory sites can yield a more accurate model and a better understanding of within-site variability. However, the use of multiple alternative representations of DNA introduces a requirement for novel algorithms that can create and test different combinations of DNA features. The Genetic Algorithm Neural Network (GANN) was designed to identify combinations of patterns that can be used to distinguish between different classes of training sequence. GANN trains a set of artificial neural networks to classify sets of sequence using either backpropagation or a genetic algorithm, and uses an 'outer genetic algorithm' to choose the best inputs from a pool of DNA features that can include sequence, structure, and weight matrix representations. When trained with a subset of upstream sequences from a whole genome, GANN was able to detect patterns such as the Shine-Dalgarno sequence in Escherichia coli K12, and sequences consistent with archaeal promoters in the archaeon Sulfolobus solfataricus P2. The Motif Genetic Algorithm (MGA) constructs motif representations by concatenating minimal units of DNA sequence and structure. This algorithm was used to model conserved patterns in DNA, including the binding sites for E. coli cyclic AMP activated protein (CAP), integration host factor (IHF), and two different promoter types recognized by alternative bacterial sigma factors. The CAP models were used to detect other putative binding sites in upstream regions of the E. coli K12 genome, while attempts to train an accurate model of IHF binding sites revealed an important role for structural representations in motif modeling.
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6

Lindberg, Stina. "Evaluation of a genomic work flow for the detection of Bacillus subtilis in animal feed and food samples." Thesis, Uppsala University, Department of Medical Biochemistry and Microbiology, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-6345.

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Bacillus anthracis is one of the most feared agents of biological warfare and causes the

deadly disease called anthrax. SVA (statens veterinärmedicinska anstalt) is working on a

project together with SLV (statens livsmedelsverk) where the target is to find rapid and

effective detection methods for Bacillus anthracis in animal feed and food samples. Bacillus

subtilis, which is harmless, was used in this study as a model organism to Bacillus anthracis.

A known concentration of vegetative Bacillus subtilis was spiked in animal feed and food

samples. The genomic work flow was based on automated DNA isolation and real time PCR.

The aim of the study was to screen for inhibitory components in the animal feed and food

samples using two different DNA isolation robots; Magnatrix 8000 and Biorobot EZ1. The

results showed that DNA of high quality was extracted from the samples with both robots.

However, the CT-value generated by the real time PCR showed considerable variation

depending on the sample matrix. Some samples, for instance egg and liver, were problematic

and gave low concentrations and high CT-values probably due to inhibitory components in the

samples. Further studies will be needed to solve these problems and optimize the methods that

were used in this study.

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7

Figueroa, Nathaniel D. "RAIDER: Rapid Ab Initio Detection of Elementary Repeats." Miami University / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=miami1390517629.

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8

Benediktsson, Elís Ingi. "Detection and analysis of megasatellites in the human genome using in silico methods." Thesis, University of Skövde, School of Humanities and Informatics, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-961.

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Megasatellites are polymorphic tandem repetitive sequences with repeat-units longer than or equal to 1000 base pairs. The novel algorithm Megasatfinder predicts megasatellites in the human genome. A structured method of analysing the algorithm is developed and conducted. The analysis method consists of six test scenarios. Scripts are created, which execute the algorithm using various parameter settings. Three nucleotide sequences are applied; a real sequence extracted from the human genome and two random sequences, generated using different base probabilities. Usability and accuracy are investigated, providing the user with confidence in the algorithm and its output. The results indicate that Megasatfinder is an excellent tool for the detection of megasatellites and that the generated results are highly reliable. The results of the complete analysis suggest alterations in the default parameter settings, presented as user guidelines, and state that artificially generated sequences are not applicable as models for real DNA in computational simulations.

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9

Lin, Ying. "Development and assessment of machine learning attributes for ortholog detection." Access to citation, abstract and download form provided by ProQuest Information and Learning Company; downloadable PDF file 0.31 Mb., 65 p, 2006. http://wwwlib.umi.com/dissertations/fullcit/3220791.

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10

Li-Sucholeiki, Xiaocheng 1968. "A technology for detecting unselected mutational spectra in human genomic DNA." Thesis, Massachusetts Institute of Technology, 1999. http://hdl.handle.net/1721.1/84743.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Division of Bioengineering and Environmental Health, 1999.
Includes bibliographical references (leaves 186-205).
by Xiaocheng Li-Suckoleiki.
Ph.D.
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11

Kannan, Anusha Aiyalu. "Detecting relevant changes in high throughput gene expression data /." Online version of thesis, 2008. http://hdl.handle.net/1850/10832.

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12

Dierckxsens, Nicolas. "Targeted organelle genome assembly and heteroplamsy detection." Doctoral thesis, Universite Libre de Bruxelles, 2018. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/277507.

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Thanks to the development of next-generation sequencing (NGS) technology, whole genome data can be readily obtained from a variety of samples. Since the massive increase in available sequencing data, the development of efficient assembly algorithms has become the new bottleneck. Almost every new released tool is based on the De Brujin graph method, which focuses on assembling complete datasets with mathematical models. Although the decreasing sequencing costs made whole genome sequencing (WGS) the most straightforward and least laborious approach of gathering sequencing data, many research projects are only interested in the extranuclear genomes. Unfortunately, few of the available tools are specifically designed to efficiently retrieve these extranuclear genomes from WGS datasets. We developed a seed-and-extend algorithm that assembles organelle circular genomes from WGS data, starting from a single short seed sequence. The algorithm has been tested on several new (Gonioctena intermedia and Avicennia marina) and public (Arabidopsis thaliana and Oryza sativa) whole genome Illumina datasets and always outperformed other assemblers in assembly accuracy and contiguity. In our benchmark, NOVOPlasty assembled all genomes in less than 30 minutes with a maximum RAM memory requirement of 16 GB. NOVOPlasty is the only de novo assembler that provides a fast and straightforward manner to extract the extranuclear sequences from WGS data and generates one circular high quality contig.Heteroplasmy, the existence of multiple mitochondrial haplotypes within an individual, has been researched across different fields. Mitochondrial genome polymorphisms have been linked to multiple severe disorders and are of interest to evolutionary studies and forensic science. By utilizing ultra-deep sequencing, it is now possible to uncover previously undiscovered patterns of intra-individual polymorphism. However, it remains challenging to determine its source. Current available software can detect polymorphic sites but are not capable of determining the link between them. We therefore developed a new method to not only detect intra-individual polymorphisms within mitochondrial and chloroplast genomes, but also to look for linkage among polymorphic sites by assembling the sequence around each detected polymorphic site. Our benchmark study shows that this method can detect heteroplasmy more accurately than any method previously available and is the first tool that is able to completely or partially reconstruct the origin sequences for each intra-individual polymorphism.
Doctorat en Sciences
info:eu-repo/semantics/nonPublished
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13

Bhattacharya, Shantanu. "A novel PCR based DNA microanalyzer system for detection of viral genome." Diss., Columbia, Mo. : University of Missouri-Columbia, 2006. http://hdl.handle.net/10355/4336.

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Thesis (Ph.D.)--University of Missouri-Columbia, 2006.
The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file viewed on (April 25, 2007) Vita. Includes bibliographical references.
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14

Bhangale, Tushar. "Small insertion-deletion polymorphisms in the human genome : characterization and automation of detection by resequencing /." Thesis, Connect to this title online; UW restricted, 2006. http://hdl.handle.net/1773/8044.

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15

Andreani, Tommaso [Verfasser]. "From DNA sequences to cell types by detecting regulatory genomic regions in sequencing data / Tommaso Andreani." Mainz : Universitätsbibliothek der Johannes Gutenberg-Universität Mainz, 2021. http://d-nb.info/1230551662/34.

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16

Beluský, Tomáš. "Detekce genomových variací." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2013. http://www.nusl.cz/ntk/nusl-236397.

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An influence of variations in human genome is perceptible at a first glance on human itself to see differences between the individuals and entire populations. Also, behavior or probability of certain diseases are influenced in large way by differences at genome's level. This work presents methods for detecting variations in the human genome that were developed after an arose of the second-generation sequencing technologies. A new tool that combines read pair and split read methods, with information about a depth of coverage was also designed and implemented. The tool was tested on simulated and real data and compared with a reference outputs.
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17

Alsulaiman, Thamer. "Detecting complex genetic mutations in large human genome data." Diss., University of Iowa, 2019. https://ir.uiowa.edu/etd/6908.

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All cellular forms of life contain Deoxyribonucleic acid (DNA). DNA is a molecule that carries all the information necessary to perform both, basic and complex cellular functions. DNA is replicated to form new tissue/organs, and to pass genetic information to future generations. DNA replication ideally yield an exact copy of the original DNA. While replication generally occurs without error, it may leave DNA vulnerable to accidental changes via mistakes made during the replication process. Those changes are called mutations. Mutations range in magnitude. Yet, mutations of any magnitude range in consequences, from no effect on the organism, to disease initiation (e.g. cancer), or even death. In this thesis, we limit our focus to mutations in human DNA, and in particular, MMBIR mutations. Recent literature in human genomics has found Microhomology-mediated break-induced replication (MMBIR) to be a common mechanism producing complex mutations in DNA. MMBIRFinder is a tool to detect MMBIR regions in Yeast DNA. Although MMBIRFinder is successful on Yeast DNA, MMBIRFinder is not capable of detecting MMBIR mutations in human DNA. Among several reasons, one major reason for its deficiency with human DNA is the amount of computations required to process human large data. Our contribution in this regard is two fold: 1) We utilize parallel computations to significantly reduce the processing time consumed by the original MMBIFinder, and address several performance degrading issues inherent in the original design; 2) We introduce a new heuristic to detect MMBIR mutations that were not detected by the original MMBIRFinder, even in the case of small sized DNA, like Yeast DNA.
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18

Zimmermann, Philipp Konstantin [Verfasser], and Christof von [Akademischer Betreuer] Kalle. "Genome‐wide detection of induced DNA double strand breaks / Philipp Konstantin Zimmermann ; Betreuer: Christof von Kalle." Heidelberg : Universitätsbibliothek Heidelberg, 2016. http://d-nb.info/118073517X/34.

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19

Forst, Jannine. "Detecting and sequencing Mycobacterium tuberculosis aDNA from archaeological remains." Thesis, University of Manchester, 2015. https://www.research.manchester.ac.uk/portal/en/theses/detecting-and-sequencing-mycobacterium-tuberculosis-adna-from-archaeological-remains(a806f3a9-8d22-4395-a1ff-a3ffbcb1c8cc).html.

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Tuberculosis has been an important disease throughout human history, shaping countless past populations. The archaeological study of the causative agents of tuberculosis, members of the Mycobacterium tuberculosis Complex (MTBC), is hindered by the non-diagnostic nature of tuberculosis-associated skeletal changes. As such, ancient DNA (aDNA) or palaeogenetic analyses have become an important tool for identifying tuberculosis in past populations. However, due to the age and variable preservation of aDNA, there are often issues with sporadic results and false negatives. The overall aim of the work presented here was to use different methods, including traditional target-specific PCR, to identify and detect tuberculosis aDNA in archaeological remains. The main objectives within this overarching aim were to first test a method called whole genome amplification (WGA), used to non-specifically amplify all the DNA within a sample, and its potential to improve the yield of aDNA from skeletal remains (Chapters 3 and 4). To determine the extent of its impact, WGA was used in a comparative context, where each archaeological sample analysed was separately subjected to two methods of MTBC detection - the traditional targeted PCR method and the same method assisted by the initial application of WGA. The results show that applying WGA before the traditional targeted PCR methodology to detect the presence of MTBC pathogens in skeletal remains is only useful and viable in some cases, likely depending on the age and preservation of the sample. The second objective was to use next generation sequencing to obtain more information on the aDNA composition of certain archaeological samples and answer questions beyond the scope of traditional target-specific PCR techniques (Chapter 5). Although most of the sequencing runs were variably unsuccessful, the composition of two samples, both known to probably contain tuberculosis aDNA, could be analysed. The samples both contained similar amounts of mycobacterial aDNA and varying amounts of both human and even potentially human intestinal flora DNA. Finally, the third objective was to determine if MTBC aDNA could be detected in a rib sample from Private William Braine of the lost Franklin Expedition using standard target-specific PCR (Chapter 6). In this case study, no evidence of tuberculosis ancient DNA was found. The work done through-out highlights the difficulties of ancient DNA research and, in Chapter 4, shows the importance of using more than a single sample to evaluate methods for application in palaeogenetic contexts.
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20

Matocha, Petr. "Efektivní hledání překryvů u NGS dat." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2017. http://www.nusl.cz/ntk/nusl-363811.

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The main theme of this work is the detection of overlaps in NGS data. The work contains an overview of NGS sequencing technologies that are the source of NGS data. In the thesis, the problem of overlapping detection is generally defined. Next, an overview of the available algorithms and approaches for detecting overlaps in NGS data is created. Principles of these algorithms are described herein. In the second part of this work a suitable tool for detecting approximate overlaps in NGS data is designed and its implementation is described herein. In conclusion, the experiments performed with this tool and the conclusions that follow are summarized and described.
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21

Delhomme, Tiffany. "Using the systematic nature of errors in NGS data to efficiently detect mutations : computational methods and application to early cancer detection." Thesis, Lyon, 2019. http://www.theses.fr/2019LYSE1098/document.

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La caractérisation exaustive des variations de l'ADN peut aider à progresser dans de nombreux champs liés à la génomique du cancer. Le séquençage nouvelle génération (NGS en anglais pour Next Generation Sequencing) est actuellement la technique la plus efficace pour déterminer une séquence ADN, du aux faibles coûts et durées des expériences comparé à la méthode de séquençage traditionnelle de Sanger. Cependant, la détection de mutations à partir de données NGS reste encore un problème difficile, en particulier pour les mutations somatiques présentes en très faible abondance comme lorsque l'on essaye d'identifier des mutations sous-clonales d'une tumeur, des mutations dérivées de la tumeur dans l'ADN circulant libre, ou des mutations somatiques dans des tissus normaux. La difficulté principale est de précisement distinguer les vraies mutations des artefacts de séquençage du au fait qu'ils atteignent des niveaux similaires. Dans cette thèse nous avons étudié la nature systématique des erreurs dans les données NGS afin de proposer des méthodologies efficaces capables d'identifier des mutations potentiellement en faible abondance. Dans un premier chapitre, nous decrivons needlestack, un nouvel outil d'appel de variants basé sur la modélisation des erreurs systématiques sur plusieurs échantillons pour extraire des mutations candidates. Dans un deuxième chapitre, nous proposons deux méthodes de filtrage des variants basées sur des résumés statistiques et sur de l'apprentissage automatique, dans le but de d'améliorer la précision de la détection des mutations par l'identification des erreurs non-systématiques. Finalement, dans un dernier chapitre nous appliquons ces approches pour développer des biomarqueurs de détection précoce du cancer en utilisant l'ADN circulant tumoral
Comprehensive characterization of DNA variations can help to progress in multiple cancer genomics fields. Next Generation Sequencing (NGS) is currently the most efficient technique to determine a DNA sequence, due to low experiment cost and time compared to the traditional Sanger sequencing. Nevertheless, detection of mutations from NGS data is still a difficult problem, in particular for somatic mutations present in very low abundance like when trying to identify tumor subclonal mutations, tumor-derived mutations in cell free DNA, or somatic mutations from histological normal tissue. The main difficulty is to precisely distinguish between true mutations from sequencing artifacts as they reach similar levels. In this thesis we have studied the systematic nature of errors in NGS data to propose efficient methodologies in order to accurately identify mutations potentially in low proportion. In a first chapter, we describe needlestack, a new variant caller based on the modelling of systematic errors across multiple samples to extract candidate mutations. In a second chapter, we propose two post-calling variant filtering methods based on new summary statistics and on machine learning, with the aim of boosting the precision of mutation detection through the identification of non-systematic errors. Finally, in a last chapter we apply these approaches to develop cancer early detection biomarkers using circulating tumor DNA
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22

Konstantinidis, Michalis. "Preimplantation genetic diagnosis : new methods for the detection of genetic abnormalities in human preimplantation embryos." Thesis, University of Oxford, 2013. http://ora.ox.ac.uk/objects/uuid:28611f65-7729-4293-9c3f-4fc3f0cc39d7.

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Preimplantation genetic diagnosis (PGD) refers to the testing of embryos produced through in vitro fertilization (IVF) in order to identify those unaffected by a specific genetic disorder or chromosomal abnormality. In this study, different methodologies were examined and developed for performance of PGD. Investigation of various whole genome amplification (WGA) methods identified multiple displacement amplification as a reliable method for genotyping single cells. Furthermore, this technology was shown to be compatible with subsequent analysis using single nucleotide polymorphism (SNP) microarrays. Compared to conventional methods used in this study to perform single cell diagnosis (e.g. multiplex PCR), WGA techniques were found to be advantageous since they streamline the development of PGD protocols for couples at high risk of transmitting an inherited disorder and simultaneously offer the possibility of comprehensive chromosome screening (CCS). This study also aimed to develop a widely applicable protocol for accurate typing of the human leukocyte antigen (HLA) region with the purpose of identifying embryos that will be HLA-identical to an existing sibling affected by a disorder that requires haematopoietic stem cell transplantation. Additionally, a novel microarray platform was developed that, apart from accurate CCS, was capable of reliably determining the relative quantity of mitochondrial DNA in polar bodies removed from oocytes and single cells biopsied from embryos. Mitochondria are known to play an important role in oogenesis and preimplantation embryogenesis and their measurement may therefore be of clinical relevance. Moreover, real-time PCR was used for development of protocols for CCS, DNA fingerprinting of sperm samples and embryos and the relative quantitation of telomere length in embryos (since shortened telomeres might be associated with reduced viability). As well as considering the role of genetics in terms of oocyte and embryo viability assessment and the diagnosis of inherited genetic disorders, attention was given to a specific gene (Phospholipase C zeta) of relevance to male infertility. A novel mutation affecting the function of the resulting protein was discovered highlighting the growing importance of DNA sequence variants in the diagnosis and treatment of infertility.
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Albrecht, Huguette. "Les produits des genes i et iv du virus de la mosaique du chou-fleur (camv)." Université Louis Pasteur (Strasbourg) (1971-2008), 1988. http://www.theses.fr/1988STR13178.

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24

Denecker, Thomas. "Bioinformatique et analyse de données multiomiques : principes et applications chez les levures pathogènes Candida glabrata et Candida albicans Functional networks of co-expressed genes to explore iron homeostasis processes in the pathogenic yeast Candida glabrata Efficient, quick and easy-to-use DNA replication timing analysis with START-R suite FAIR_Bioinfo: a turnkey training course and protocol for reproducible computational biology Label-free quantitative proteomics in Candida yeast species: technical and biological replicates to assess data reproducibility Rendre ses projets R plus accessibles grâce à Shiny Pixel: a content management platform for quantitative omics data Empowering the detection of ChIP-seq "basic peaks" (bPeaks) in small eukaryotic genomes with a web user-interactive interface A hypothesis-driven approach identifies CDK4 and CDK6 inhibitors as candidate drugs for treatments of adrenocortical carcinomas Characterization of the replication timing program of 6 human model cell lines." Thesis, université Paris-Saclay, 2020. http://www.theses.fr/2020UPASL010.

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Plusieurs évolutions sont constatées dans la recherche en biologie. Tout d’abord, les études menées reposent souvent sur des approches expérimentales quantitatives. L’analyse et l’interprétation des résultats requièrent l’utilisation de l’informatique et des statistiques. Également, en complément des études centrées sur des objets biologiques isolés, les technologies expérimentales haut débit permettent l’étude des systèmes (caractérisation des composants du système ainsi que des interactions entre ces composants). De très grandes quantités de données sont disponibles dans les bases de données publiques, librement réutilisables pour de nouvelles problématiques. Enfin, les données utiles pour les recherches en biologie sont très hétérogènes (données numériques, de textes, images, séquences biologiques, etc.) et conservées sur des supports d’information également très hétérogènes (papiers ou numériques). Ainsi « l’analyse de données » s’est petit à petit imposée comme une problématique de recherche à part entière et en seulement une dizaine d’années, le domaine de la « Bioinformatique » s’est en conséquence totalement réinventé. Disposer d’une grande quantité de données pour répondre à un questionnement biologique n’est souvent pas le défi principal. La vraie difficulté est la capacité des chercheurs à convertir les données en information, puis en connaissance. Dans ce contexte, plusieurs problématiques de recherche en biologie ont été abordées lors de cette thèse. La première concerne l’étude de l’homéostasie du fer chez la levure pathogène Candida glabrata. La seconde concerne l’étude systématique des modifications post-traductionnelles des protéines chez la levure pathogène Candida albicans. Pour ces deux projets, des données « omiques » ont été exploitées : transcriptomiques et protéomiques. Des outils bioinformatiques et des outils d’analyses ont été implémentés en parallèle conduisant à l’émergence de nouvelles hypothèses de recherche en biologie. Une attention particulière et constante a aussi été portée sur les problématiques de reproductibilité et de partage des résultats avec la communauté scientifique
Biological research is changing. First, studies are often based on quantitative experimental approaches. The analysis and the interpretation of the obtained results thus need computer science and statistics. Also, together with studies focused on isolated biological objects, high throughput experimental technologies allow to capture the functioning of biological systems (identification of components as well as the interactions between them). Very large amounts of data are also available in public databases, freely reusable to solve new open questions. Finally, the data in biological research are heterogeneous (digital data, texts, images, biological sequences, etc.) and stored on multiple supports (paper or digital). Thus, "data analysis" has gradually emerged as a key research issue, and in only ten years, the field of "Bioinformatics" has been significantly changed. Having a large amount of data to answer a biological question is often not the main challenge. The real challenge is the ability of researchers to convert the data into information and then into knowledge. In this context, several biological research projects were addressed in this thesis. The first concerns the study of iron homeostasis in the pathogenic yeast Candida glabrata. The second concerns the systematic investigation of post-translational modifications of proteins in the pathogenic yeast Candida albicans. In these two projects, omics data were used: transcriptomics and proteomics. Appropriate bioinformatics and analysis tools were developed, leading to the emergence of new research hypotheses. Particular and constant attention has also been paid to the question of data reproducibility and sharing of results with the scientific community
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Yan-Cho, Lee, and 李元晫. "Detection of genomic DNA alternations in sodium arsenite-treated lymphoblastoid cells by random amplified polymorphic DNA assay." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/35075218998894624845.

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碩士
東海大學
生物學系
92
Abstract Epidemiologic studies demonstrated that long-term exposure to arsenic induces many human diseases, including blackfoot disease, atherosclerosis, and cancers. Although evidences show an association between arsenic and cancer, the molecular mechanism is still unclear. It is widely accepted that cancer results from the accumulation of mutations in the genes. Sodium arsenite has been shown to induce oxidative DNA damages and DNA-protein crosslinks. In this study, we used the random amplified polymorphic DNA (RAPD) assay with ninety arbitrary primers to evaluate the effects on the genomic DNA of human lymphoblastoid cells exposed to sodium arsenite. The main changes in RAPD profiles following sodium arsenite treatments were a decrease and an increase in band intensity. Two RAPD primers (D11 and F1) were more discriminated the RAPD profiles between sodium arsenite-treated and control genomic DNA. The sequences of these loci amplified with primers D11 and F1 showed highly similar to human RB1CC1 and PACE4 genes. The DNA markers were purified for the molecular detection of sodium arsenite-induced DNA damage by nucleic acid hybridization. To confirm the effect of sodium arsenite on RB1CC1 and PACE4 genes, we examined the expression of these two genes by Northern blot and RT-PCR analysis. Sodium arsenite treatment could significantly up-regulate the expression of RB1CC1 in human lymphoblastoid cells. Taken together, our results demonstrated, for the first time, that RAPD is a good tool for the detection of genomic DNA alternations and direct screening of new molecular markers related to sodium arsenite-induced carcinogenesis
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26

Hung, Wan-Yu, and 洪宛榆. "Identification of Genome-wide DNA Methylation Alterations in Colorectal Tumors and Its Application in Early Detection of Cell-free DNA of Plasma." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/9n6db3.

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27

"The study and detection of human papillomavirus (HPV) genome in two cervical carcinoma cell lines by the use of hybridization techniques." Chinese University of Hong Kong, 1990. http://library.cuhk.edu.hk/record=b5886639.

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Abstract:
Tin-hung Ho.
Thesis (M.Phil.)--Chinese University of Hong Kong, 1990.
Bibliography: leaves 137-151.
ACKNOWLEDGEMENT --- p.1
CONTENT --- p.3
ABBREVIATIONS --- p.7
ABSTRACT --- p.8
Chapter CHAPTER 1 --- INTRODUCTION --- p.10
Chapter CHAPTER 2 --- LITERATURE REVIEW
Chapter 2.1 --- The cervix and cervical cancer --- p.12
Chapter 2.2 --- Human papillomaviruses --- p.23
Chapter 2.3 --- Culture of cancer cells --- p.36
Chapter 2.4 --- Methods for the detection of HPV infection --- p.40
Chapter CHAPTER 3 --- MATERIALS AND METHODS
Chapter 3.1 --- Characterization of cervical carcinoma cell lines
Chapter 3.1.1 --- Materials and solutions --- p.47
Chapter 3.1.2 --- Establishment of cervical carcinoma cell lines --- p.50
Chapter 3.1.3 --- Morphological studies of cervical carcinoma cells --- p.52
Chapter 3.1.4 --- Examination of cervical carcinoma cells cultured on collagen gel --- p.54
Chapter 3.1.5 --- Growth kinetics study --- p.55
Chapter 3.1.6 --- Plating efficiency test --- p.56
Chapter 3.1.7 --- Spheroid formation assay --- p.56
Chapter 3.1.8 --- Chromosome number study --- p.57
Chapter 3.2 --- Immunocytochemical studies
Chapter 3.2.1 --- Materials and solutions --- p.58
Chapter 3.2.2 --- Immunocytochemical test for keratin --- p.59
Chapter 3.2.3 --- Test for HPV capsid antigens --- p.60
Chapter 3.3 --- Molecular studies of HPV in cervical carcinoma cells
Chapter 3.3.1 --- Materials and solutions --- p.62
Chapter 3.3.2 --- Preparation of HPV DNA probes --- p.66
Chapter 3.3.3 --- DNA extraction from the cervical carcinoma cells --- p.74
Chapter 3.3.4 --- Detection of HPV DNA sequences by the use of hybridization techniques --- p.76
Chapter 3.3.5 --- Copy number and physical state studies of HPV --- p.81
Chapter 3.3.6 --- Study of the transcriptional activity of HPV DNA in cultured cervical carcinoma cells --- p.83
Chapter CHAPTER 4 --- RESULTS
Chapter 4.1 --- Characterization of cervical carcinoma cell lines
Chapter 4.1.1 --- Morphological studies --- p.89
Chapter 4.1.2 --- Examination of cervical carcinoma cells cultured on collagen gel --- p.90
Chapter 4.1.3 --- Growth kinetics study --- p.93
Chapter 4.1.4 --- Plating efficiency test --- p.94
Chapter 4.1.5 --- Spheroid formation assay --- p.95
Chapter 4.1.6 --- Chromosome number study --- p.98
Chapter 4.2 --- Immunocytochemical studies
Chapter 4.2.1 --- Immunocytochemical test for keratin --- p.99
Chapter 4.2.2 --- Test for HPV capsid antigen --- p.99
Chapter 4.3 --- Molecular studies of HPV in cervical carcinoma cell lines
Chapter 4.3.1 --- Preparation of HPV DNA probes --- p.101
Chapter 4.3.2 --- Detection of HPV DNA by the use of hybridization techniques --- p.102
Chapter 4.3.3 --- Copy number and physical state studies --- p.105
Chapter 4.3.4 --- Analysis of the transcriptional activity --- p.108
Chapter CHAPTER 5 --- DISCUSSIONS
Chapter 5.1 --- Characterization of cervical carcinoma cell lines
Chapter 5.1.1 --- Morphological features of two cervical carcinoma cell lines --- p.110
Chapter 5.1.2 --- Other characteristics of the cell lines --- p.112
Chapter 5.2 --- Immunocytochemical studies
Chapter 5.2.1 --- Test for keratin antigens --- p.117
Chapter 5.2.2 --- Test for HPV capsid antigens --- p.117
Chapter 5.3 --- Molecular studies of HPV in cervical carcinoma cell lines
Chapter 5.3.1 --- Establishment of methods --- p.121
Chapter 5.3.2 --- Detection of HPV DNA sequences by nucleic acid hybridizations --- p.123
Chapter 5.3.3 --- Copy number and physical state studies --- p.128
Chapter 5.3.4 --- Transcriptional analysis of HPV DNA in cervical carcinoma cell lines --- p.132
CONCLUSION --- p.134
REFERENCES --- p.137
ILLUSTRATIONS --- p.152
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