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PEPDB Construction and Large-Scale Analysis of ESTSShen, Ling 07 1900 (has links)
The Protist EST program (PEP) aims to explore the diversity of eukaryotic genomes, in a systematic and comprehensive way. A main element of the PEP initiative is to establish a database, the Protist EST Database (PEPdb), which is the centerpiece of the PEP collaboration. The major functions of the PEPdb are management of the data generated by
PEP, analysis of these data, and to allow collected sequence information to be accessed via the Internet by PEP members or other users. In this project, a consistent and easy to use relational database was implemented. All information about PEP members, Publications, Libraries and ESTs can be stored in the database system. The operations are achieved by
a friendly user interface. This database stores about 10000 records and is displayed on the web site "http://info.biology.mcmaster.ca/ling/estHome.html" for demonstration. An analysis of ESTs from the ciliated protozoan Tetrahymena thermophila was undertaken. A total of 3740 non-redundant gene assemblies and singletons from TIGR were analyzed. These sequences have been compared against the NCBI non-redundant protein and nucleotide databases using BLASTX and BLASTN to identify putative genes. Of 850 highly significant matches with an expect value cut-off of 10^-20 , 35.5% represent genes previously cloned from T. thermophila, and 64.5% had significant similarity to genes from other organisms deposited in the NCBI. There are 26 sequences (3.1%) that matched signal transduction proteins, including Rac, Ras, MAPK, ERK1, PKC, cAMP and 14-3-3 (a protein involved in signal transduction, exocytosis and cell cycle regulation). This result indicates that T. thermophila likely encodes the MAPK/ERK signaling pathway. About 53
sequences (6.2%) matched to cytoskeleton proteins which were divided into two groups. The first group matched genes coding for microtubules, especially to tubulin genes. The other group matched to microfilament genes including one actin, three actin-related and one profilin proteins. There were no sequences similar to intermediate filaments. Comparison of the EST counts from one gene provide absolute estimates of mRNA expression levels. The most abundant genes represented are enolase, SerH3 and Tubulin. Among 850 highly significant similarities, 196 were restricted to the ciliophora. GRL and SerH are ciliate-specific genes. There were 508 sequences that had highly significant matches (expect
value < 10^-20) to human genes. Approximately 189 of them were present in humans but not found in the completely sequenced Saccharomyces cerevisiae. Based on Venn diagram analysis, T. thermophila contains abundant Eukaryotic specific proteins and many prokaryotic-like genes, and some metabolic enzymes in T. thermophila are also present in
plants. These results support the fact that T. thermophila is an excellent unicellular model system for gene discovery and functional analysis. / Thesis / Master of Science (MS)
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Interactions cytokiniques dans le microenvironnement inflammatoire : analyse à large échelle de la réponse aux Interférons de Type I lors la de polarisation des Lymphocytes T auxiliaires / Modulation of cytokine response by microenvironment : large-scale analysis of Type IFN response during Human T Helper cells differentiationTouzot, Maxime 27 March 2013 (has links)
Les interférons de Type I (IFN) sont des cytokines produites par les cellules en réponse à une infection virale. Les IFNs ont des effets pleïotropiques et parfois paradoxaux, protecteur ou néfaste pour l’immunité Innée ou adaptative. Certains facteurs intrinsèques (type cellulaire) peuvent expliquer une partie ces discordances. Mon travail de thèse s’est intéressé à l‘effet du microenvironnement cytokinique sur la réponse IFN. En utilisant des analyses à large échelle, nous avons étudié la réponse IFN dans 4 contextes de polarisation des lymphocytes T auxiliaires (Th). Nous avons identifié 1/ un programme de transcription conservé et 2/ une réponse IFN flexible, modulant spécifiquement les principales fonctions des Th (cytokines, chemokines) en fonction du contexte polarisant. La réponse antivirale apparait aussi flexible avec une moins bonne protection des Th2 et Th17 contre l’infection par HIV-1et HIV-2. Nos résultats suggèrent que l’environnement cytokinique contrôle en partie la réponse IFN et peut ainsi moduler cette dernière dans différents contextes physiopathologiques. / Type I IFN (IFN) are innate cytokines produced by host cells during viral infection. Ithas pleiotropic and sometimes opposing, protective or detrimental effects, on both innateand adaptive immunity that remain poorly understood. Parts of IFN response may be explain by intrinsic effect (cell-‐specificity). My thesis was focused on the effect of the microenvironment, as present during T Helper cell differentiation, on IFN response. Using a systems level approach, we studied IFN responses during Four Human T Helper cell differentiation. We identified 1/ a conserved IFN-‐induced transcriptional program comprising mostly antiviral genes 2/ a flexible IFN response, leading to a different pattern of chemokine and cytokine induction by IFN in distinct Th environments. Antiviral response was also flexible with a lesser protection to HIV-1 and HIV-2 infection in Th2 and Th17 contexts. Our in vitro results suggested that environmental control might shape the effects of IFN in different physiopathological contexts.
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MODELING LARGE-SCALE CROSS EFFECT IN CO-PURCHASE INCIDENCE: COMPARING ARTIFICIAL NEURAL NETWORK TECHNIQUES AND MULTIVARIATE PROBIT MODELINGYang, Zhiguo 01 January 2015 (has links)
This dissertation examines cross-category effects in consumer purchases from the big data and analytics perspectives. It uses data from Nielsen Consumer Panel and Scanner databases for its investigations. With big data analytics it becomes possible to examine the cross effects of many product categories on each other. The number of categories whose cross effects are studied is called category scale or just scale in this dissertation. The larger the category scale the higher the number of categories whose cross effects are studied. This dissertation extends research on models of cross effects by (1) examining the performance of MVP model across category scale; (2) customizing artificial neural network (ANN) techniques for large-scale cross effect analysis; (3) examining the performance of ANN across scale; and (4) developing a conceptual model of spending habits as a source of cross effect heterogeneity. The results provide researchers and managers new knowledge about using the two techniques in large category scale settings The computational capabilities required by MVP models grow exponentially with scale and thus are more significantly limited by computational capabilities than are ANN models. In our experiments, for scales 4, 8, 16 and 32, using Nielsen data, MVP models could not be estimated using baskets with 16 and more categories. We attempted to and could calibrate ANN models, on the other hand, for both scales 16 and 32. Surprisingly, the predictive results of ANN models exhibit an inverted U relationship with scale. As an ancillary result we provide a method for determining the existence and extent of non-linear own and cross category effects on likelihood of purchase of a category using ANN models. Besides our empirical studies, we draw on the mental budgeting model and impulsive spending literature, to provide a conceptualization of consumer spending habits as a source of heterogeneity in cross effect context. Finally, after a discussion of conclusions and limitations, the dissertation concludes with a discussion of open questions for future research.
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Development and evaluation of an interactive e-module on Central Limit TheoremHolovchenko, Anastasiia 04 May 2023 (has links)
No description available.
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Ecological determinants of roe deer (Capreolus capreolus) spatial behavior and movement in limiting conditions / Déterminants écologiques du comportement spatial et des mouvements des chevreuils en conditions limitantesOssi, Federico 13 January 2015 (has links)
Pour la grande majorité des grands herbivores vivant en régions tempérées, l'hiver est la saison la plus limitante à cause des effets combinés du manque de ressources et de la sévérité des conditions climatiques. Les espèces qui ne développent pas d'adaptations morphologiques ou physiologiques particulières pour faire face à la sévérité de l'hiver doivent mettre en place des mouvements et des tactiques d'utilisation de l'espace appropriés (comme par exemple les migrations). Plus spécifiquement, ces patrons d'utilisation de l'espace peuvent émerger à différentes échelles spatio-temporelles pour permettre aux individus d'accéder aux ressources dont ils ont besoin et d'échapper aux conditions climatiques défavorables. Ainsi, ces patrons d'utilisation de l'espace déterminent le sort des individus et la dynamique des populations. Une compréhension détaillée de la relation entre les facteurs limitants durant l'hiver et la réponse des animaux en termes de mouvements est prépondérante pour préserver et gérer les populations d'ongulés sauvages avec succès, tout spécialement dans le contexte actuel de changements climatiques rapides qui induisent des modifications importantes dans le paysage et la distribution des ressources (par exemple changement de patrons de couverture neigeuse en hiver). La comparaison de tactiques de mouvements sous différents scénarios de conditions environnementales, par exemple au moyen d'analyses à vaste échelle de l'aire de distribution de l'espèce cible, représente une approche pertinente pour mieux comprendre comment les mouvements des animaux répondent aux changements dans le paysage. Le chevreuil (Capreoluscapreolus) est une espèce modèle particulièrement intéressante pour étudier ces questions parce que la distribution de cette espèce couvre la plupart des pays d'Europe, grâce à sa forte plasticité écologique / For the majority of large ungulates living in temperate regions winter is the limiting season, because of the combined effects of lack of resource availability and severity of climatic conditions. Those species that did not develop any particular morphological and physiological adaptation to cope with winter severity may adopt movement and space use tactics instead (like e.g. migration). Specifically, these space use patterns may emerge at different spatiotemporal scales to allow individuals to accede the resources they need and escape unfavourable conditions, thus determining both individual fate and population dynamics. A detailed understanding of the relationship between limiting factors in wintertime, and individual movement response, is remarkable to preserve and manage wildlife successfully, especially in the context of fast-occurring climate change that induces important alterations in landscape and resource distribution (e.g. changes of snow cover patterns). The comparison of movement tactics under different environmental scenarios, e.g. by means of large –scale analysis at the species distribution range, represents a valuable approach to work in that direction and to assess the effects of landscape alteration on individual movement. Roe deer (Capreolus capreolus) is an excellent model species to investigate these issues, because its distribution range covers most of Europe, thanks to its high ecological plasticity. For those populations that live in northern and mountain environments, winter is the limiting season because roe deer lack any morphological and physiological adaptations to cope with winter severity. In spite of the adoption of specific movement tactics such as partial migration from summer to winter ranges, roe deer may still face limiting conditions in some areas of the distribution range exposed to winter severity
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Efron’s Method on Large Scale Correlated Data and Its RefinementsGhoshal, Asmita 11 August 2023 (has links)
No description available.
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[en] TOPSIM: A PLUGIN-BASED FRAMEWORK FOR LARGE-SCALE NUMERICAL ANALYSIS / [pt] TOPSIM: UM SISTEMA BASEADO EM PLUGIN PARA ANÁLISE NUMÉRICA EM LARGA ESCALALEONARDO SEPERUELO DUARTE 12 January 2017 (has links)
[pt] Métodos computacionais em engenharia são usados na solução de problemas físicos que não possuem solução analítica ou sua perfeita representação matemática é inviável. Técnicas de métodos numéricos, incluindo o amplamente usado método dos elementos finitos, podem exigir a solução de sistemas lineares com centenas de milhares de equações, demandando altos recursos computacionais (memória e tempo). Nesta tese, nós apresentamos um sistema baseado em plugins para análise numérica em larga escala. O sistema é usado como uma ferramenta original na solução de problemas de otimização topológica usando o método dos elementos finitos com milhões de elementos. Nossa estratégia utiliza uma técnica elemento-por-elemento para implementar um código altamente paralelo para um solver iterativo com baixo consumo de memória. Além disso, a abordagem de plugin proporciona um ambiente completamente flexível e fácil de estender, onde diferentes aplicações, exigindo diferentes tipos de elementos finitos, materiais, solvers lineares e formulações podem ser desenvolvidos e melhorados. O kernel do sistema é mínimo, com apenas um módulo gerenciador de plugin, responsável por carregar os plugins desejados em tempo real usando um arquivo de configuração de entrada. Todas as funcionalidades necessárias para uma determinada aplicação são definidas dentro dos plugins, sem a necessidade de mudar o kernel. Plugins podem disponibilizar ou exigir interfaces adicionais especializadas, onde outros plugins podem ser conectados para compor um sistema mais complexo e completo. Nós apresentamos resultados para uma análise estrutural estática linear elástica e para uma análise estrutural de otimização topológica. As simulações utilizam elementos Q4, hexagonal (Brick8) e prisma hexagonal (Honeycomb), com solvers diretos e iterativos usando computação sequencial, paralela e distribuída. Nós investigamos o desempenho com relação ao uso de memória e escalabilidade da solução para problemas com diferentes tamanhos, de exemplos pequenos a muito grandes em apenas uma máquina e em um cluster. Foi simulado um exemplo de análise estática linear elástica com 500 milhões de elementos em 300 máquinas. / [en] Computational methods in engineering are used to solve physical problems that do not have analytical solution or their perfect mathematical representation is unfeasible. Numerical techniques, including the largely used finite element method, require the solution of linear systems with hundreds of thousands equations, demanding high computational resources (memory and time). In this thesis, we present a plugin-based framework for large-scale numerical analysis. The framework is used as an original tool to solve topology optimization problems using the finite element method with millions of elements. Our strategy uses an element-by-element technique to implement a highly parallel code for an iterative solver with low memory consumption. Besides, the plugin approach provides a fully flexible and easy to extend environment, where different types of applications, requiring different types of finite elements, materials, linear solvers, and formulations, can be developed and improved. The kernel of the framework is minimum with only a plugin manager module, responsible to load the desired plugins during runtime using an input configuration file. All the features required for a specific application are defined inside plugins, with no need to change the kernel. Plugins may provide or require additional specialized interfaces, where other plugins may be connected to compose a more complex and complete system. We present results for a structural linear elastic static analysis and for a structural topology optimization analysis. The simulations use elements Q4, hexahedron (Brick8), and hexagonal prism (Honeycomb), with direct and iterative solvers using sequential, parallel and distributed computing. We investigate the performance regarding the use of memory and the scalability of the solution for problems with different sizes, from small to very large examples on a single machine and on a cluster. We simulated a linear elastic static example with 500 million elements on 300 machines.
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