The development of high-throughput next-generation sequencing (NGS) techniques produces massive amount of data, allowing the identification of biomarkers in early disease diagnosis and driving the transformation of most disciplines in biology and medicine. A greater concentration is needed in developing novel, powerful, and efficient tools for NGS data analysis. This dissertation focuses on modeling ``omics'' data in various NGS applications with a primary goal of developing novel statistical methods to identify sequence variants, find transcription factor (TF) binding patterns, and decode the relationship between TF and gene expression levels. Accurate and reliable identification of sequence variants, including single nucleotide polymorphisms (SNPs) and insertion-deletion polymorphisms (INDELs), plays a fundamental role in NGS applications. Existing methods for calling these variants often make simplified assumption of positional independence and fail to leverage the dependence of genotypes at nearby loci induced by linkage disequilibrium. We propose vi-HMM, a hidden Markov model (HMM)-based method for calling SNPs and INDELs in mapped short read data. Simulation experiments show that, under various sequencing depths, vi-HMM outperforms existing methods in terms of sensitivity and F1 score. When applied to the human whole genome sequencing data, vi-HMM demonstrates higher accuracy in calling SNPs and INDELs. One important NGS application is chromatin immunoprecipitation followed by sequencing (ChIP-seq), which characterizes protein-DNA relations through genome-wide mapping of TF binding sites. Multiple TFs, binding to DNA sequences, often show complex binding patterns, which indicate how TFs with similar functionalities work together to regulate the expression of target genes. To help uncover the transcriptional regulation mechanism, we propose a novel nonparametric Bayesian method to detect the clustering pattern of multiple-TF bindings from ChIP-seq datasets. Simulation study demonstrates that our method performs best with regard to precision, recall, and F1 score, in comparison to traditional methods. We also apply the method on real data and observe several TF clusters that have been recognized previously in mouse embryonic stem cells. Recent advances in ChIP-seq and RNA sequencing (RNA-Seq) technologies provides more reliable and accurate characterization of TF binding sites and gene expression measurements, which serves as a basis to study the regulatory functions of TFs on gene expression. We propose a log Gaussian cox process with wavelet-based functional model to quantify the relationship between TF binding site locations and gene expression levels. Through the simulation study, we demonstrate that our method performs well, especially with large sample size and small variance. It also shows a remarkable ability to distinguish real local feature in the function estimates. / Doctor of Philosophy / The development of high-throughput next-generation sequencing (NGS) techniques produces massive amount of data and bring out innovations in biology and medicine. A greater concentration is needed in developing novel, powerful, and efficient tools for NGS data analysis. In this dissertation, we mainly focus on three problems closely related to NGS and its applications: (1) how to improve variant calling accuracy, (2) how to model transcription factor (TF) binding patterns, and (3) how to quantify of the contribution of TF binding on gene expression. We develop novel statistical methods to identify sequence variants, find TF binding patterns, and explore the relationship between TF binding and gene expressions. We expect our findings will be helpful in promoting a better understanding of disease causality and facilitating the design of personalized treatments.

The diploma thesis focuses on design of the information system for the department of medical transport service, which is part of the hospital. This thesis describes the theoretical knowledge necessary for analysis and custom design, is also concerned with the analysis of the current state of processes and information system. Last but not least, based on the analysis and the requirements lays down suggestions for improvement of the information system and design of optimal information system, that effectively supports the processes and enables its users to work more efficiently.

Les simulations numériques des équations d’Euler deux-fluides réalisé sur des maillages grossiers éliminent les structures fins d’écoulement gaz-solide dans les lits fluidisés. Pour précisément estimer l’hydrodynamique globale de lit, il faut proposer une modélisation qui prend en compte les effets de structure non-résolue. Dans ce but, les maillages sont raffinés pour obtenir le résultat de simulation pleinement résolue ce que les grandeurs statistiques ne modifient plus avec un autre raffinement pour le lit fluidisé périodique dilué gaz-particules sur une géométrie 3D cartésienne et ce résultat est utilisé pour tests "a priori". Les résultats de tests "a priori" montrent que l’équation filtrée de la quantité de mouvement est effectuée mais il faut prendre en compte le flux de la fraction volumique de solide de sous-maille en raison de l’interaction locale de la vitesse du gaz et la fraction volumique de solide pour la force traniée. Nous proposons les modèles fonctionnels et structurels pour le flux de la fraction volumique de solide de sous-maille. En plus, les modèles fermetures du tenseur de sous-maille de la phase dispersée sont similaires aux modèles classiquement utilisés en écoulement turbulent monophasique. Tous les modèles sont validés par test "a priori" et "a posteriori" / Eulerian two fluid approach is generally used to simulate gas-solid flows in industrial circulating fluidized beds. Because of limitation of computational resources, simulations of large vessels are usually performed by using too coarse grid. Coarse grid simulations can not resolve fine flow scales which can play an important role in the dynamic behaviour of the beds. In particular, cancelling out the particle segregation effect of small scales leads to an inadequate modelling of the mean interfacial momentum transfer between phases and particulate shear stresses by secondary effect. Then, an appropriate modelling ac counting for influences of unresolved structures has to be proposed for coarse-grid simu-lations. For this purpose, computational grids are refined to get mesh-independent result where statistical quantities do not change with further mesh refinement for a 3-D peri-odic circulating fluidized bed. The 3-D periodic circulating fluidized is a simple academic configuration where gas-solid flow conducted with A-type particles is periodically driven along the opposite direction of the gravity. The particulate momentum and agitation equations are filtered by the volume averaging and the importance of additional terms due to the averaging procedure are investigated by budget analyses using the mesh independent result. Results show that the filtered momentum equation of phases can be computed on coarse grid simulations but sub-grid drift velocity due to the sub-grid correlation between the local fluid veloc- ity and the local particle volume fraction and particulate sub-grid shear stresses must be taken into account. In this study, we propose functional and structural models for sub- grid drift velocity, written in terms of the difference between the gas velocity-solid volume fraction correlation and the multiplication of the filtered gas velocity with the filtered solid volume fraction. Particulate sub-grid shear stresses are closed by models proposed for single turbulent flows. Models’ predictabilities are investigated by a priori tests and they are validated by coarse-grid simulations of 3-D periodic circulating, dense fluidized beds and experimental data of industrial scale circulating fluidized bed in manner of a posteriori tests