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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Výskyt polymorfismů v genu \kur{MTHFR} a jejich možná asociace se sterilitou a problematikou opakovaných spontánních potratů v české populaci

STRÁSKÁ, Markéta January 2018 (has links)
The thesis analyses the pairs that have not been able to conceive, or they have been diagnosed with sterility and they undergo an assisted reproductive technology as a possible treatment, or they have suffered from the recurrent pregnancy loss. The data for the second part of this study were gathered from 2014 to 2018 and have been provided by genetic laboratory GENLABS from České Budějovice. This part tries to statistically express prevalence of the two most studied MTHFR gene polymorphisms among Czech.
2

Diversité et déterminisme génétique de la recombinaison méiotique chez Saccharomyces cerevisiae / Diversity and genetic determinsim of meiotic recombination rate in Saccharomyces cerevisiae

Raffoux, Xavier 06 November 2018 (has links)
L’agriculture moderne doit assurer notre sécurité alimentaire dans le contexte d’un changement climatique qui entraîne une baisse des rendements. Une meilleure compréhension des facteurs contrôlant la recombinaison méiotique ouvrirait la voie à la modification du nombre et de la répartition des crossing-overs, ce qui permettrait une localisation plus précise des facteurs génétiques contrôlant les caractères d’intérêt agronomique et faciliterait le pyramidage d’allèles favorables au sein d’un même génotype élite. Pendant ma thèse, j’ai développé une méthode de mesure à haut débit de la recombinaison chez la levure Saccharomyces cerevisiae pour étudier la diversité de la recombinaison et de l’interférence au sein d’une collection de 24 souches représentatives de la diversité de l’espèce ainsi qu’au sein d’un dispositif di-allèle à cinq parents. Les résultats montrent un nombre moyen de crossing-overs par méiose compris entre 24 et 61, ce qui est plus élevé que chez la majorité des autres espèces. Plus particulièrement, les profils de recombinaison diffèrent entre souches, atteignant un écart d’un facteur 9 dans certaines régions. Les souches originaires d’habitats peu stables n’ont cependant pas un niveau de recombinaison plus élevé que les souches originaires d’environnements stables. En outre, la plupart des souches montrent de l’interférence dont la force est corrélée positivement avec le niveau de recombinaison. L’étude de la relation entre niveau de recombinaison et similarité de séquence entre homologues, à différentes échelles locales ou globales, indique que la recombinaison est contrôlée à la fois par des éléments cis et des facteurs trans. Par ailleurs, l’hétérozygotie chez les hybrides a un effet négatif sur le niveau de recombinaison, mais les homozygotes ont aussi un niveau de recombinaison réduit par un effet de dépression de consanguinité. Ce travail permettra maintenant d’étudier la réponse de la recombinaison à la sélection et de détecter les QTL de nombre de crossing-overs, afin d’identifier des gènes qui contrôlent la recombinaison. / Modern agriculture must ensure food security in a context of climate change that will lower yields. A better understanding of the factors controlling meiotic recombination could pave the way to modifying the number and distribution of crossing-over, which would allow a more precise localization of genetic factors controlling agronomic traits, and facilitate gene pyramiding in selection programs. During my thesis, I developed a method for high-throughput measurement of recombination rates in the yeast Saccharomyces cerevisiae. This allowed me to study the diversity of recombination and interference in a collection of 24 strains representing most of the diversity of the species, as well as within a five-parent di-allele design. The results show an average number of crossovers per meiosis ranging between 24 and 61, higher than in the majority of other species. Furthermore, recombination patterns differ between strains, and ratios of local recombination rates show 9-fold differences in some regions. Strains from unstable habitats, however, do not have a higher level of recombination than those from stable environments. In addition, most strains show interference whose strength is positively correlated with the level of recombination. The study of the relationship between recombination rate and sequence similarity between homologs at different scales (from local to global) indicates that recombination is controlled by both cis elements and trans factors. Lastly, heterozygosity in hybrids has a negative effect on crossing-over, but homozygotes also have a reduced level of recombination due to inbreeding depression. This work will now be used to study the response of recombination to selection and to detect QTL of crossover number in order to identify genes controlling recombination.
3

Redukce šumu audionahrávek pomocí hlubokých neuronových sítí / Audio noise reduction using deep neural networks

Talár, Ondřej January 2017 (has links)
The thesis focuses on the use of deep recurrent neural network, architecture Long Short-Term Memory for robust denoising of audio signal. LSTM is currently very attractive due to its characteristics to remember previous weights, or edit them not only according to the used algorithms, but also by examining changes in neighboring cells. The work describes the selection of the initial dataset and used noise along with the creation of optimal test data. For network training, the KERAS framework for Python is selected. Candidate networks for possible solutions are explored and described, followed by several experiments to determine the true behavior of the neural network.
4

Redukce šumu audionahrávek pomocí hlubokých neuronových sítí / Audio noise reduction using deep neural networks

Talár, Ondřej January 2017 (has links)
The thesis focuses on the use of deep recurrent neural network, architecture Long Short-Term Memory for robust denoising of audio signal. LSTM is currently very attractive due to its characteristics to remember previous weights, or edit them not only according to the used algorithms, but also by examining changes in neighboring cells. The work describes the selection of the initial dataset and used noise along with the creation of optimal test data. For creation of the training network is selected KERAS framework for Python and are explored and discussed possible candidates for viable solutions.

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