The introduction of the single currency (Euro) in Europe has been referred to as the ‘world’s largest economic experiment’ and has led to major research on the effects of the adoption of a common currency on economic activity with considerable emphasis on its effect on trade flows at the macroeconomic level. However, the investigation of the euro effect on individual sectors has received very little attention and this provides the motivation for the research. The main contribution of this thesis is to the sectoral analysis of the single currency’s effect on bi-lateral trade flows, specifically the effects on the transport equipment manufacturing sector. In order to achieve this, a comparison of the different estimation methods applied in the gravity model literature will be employed to investigate this effect and to identify the factors affecting trade in this sector. This study uses a panel data set which comprises the most recent information on bilateral trade for the EU15 countries from 1990 to 2008. This research aims to build on the results obtained in previous studies by employing a more refined empirical methodology and associated tests. The purpose of the tests is to ensure that the euro’s effect on trade is isolated from the other pro- trade policies of the European integration processes, particularly the introduction of the Single Market. The desirable feature of this approach is that, while other studies limit their attention to a particular issue (zero trade flow, time trend, sectoral analysis, cross-correlation, etc.), very few, if any, apply a selection of techniques. Overall, the results demonstrate that the single currency’s effect on trade in this sector is limited with only the fixed effects formulation with year dummy variables showing a significant positive effect of the euro. An obvious policy implication for countries looking to adopt a single currency is that they should be cautious regarding the potential for growth in intra-bloc trade in a particular sector, although they will benefit from the on-going process of integration.

Un des défis fondamentaux de la biologie moderne est une meilleure compréhension des mécanismes de régulation de l'expression des gènes, dont dépendent notamment le fonctionnement et la différentiation des cellules. En outre, leurs dérèglements peuvent être à l'origine de pathologies comme par exemple les cancers. Les technologies haut-débit de l'ère post-génomique permettent la production massive de données concernant notamment l'expression des gènes, les sites de fixation des facteurs de transcription et l'état de la chromatine. Ces données sont une mine d'informations pour l'étude des mécanismes de régulation. Cependant, la quantité et l'hétérogénéité de ces données soulèvent de nombreuses problématiques bioinformatiques liées à l'accès, la visualisation, l'analyse et l'intégration de celles-ci.Cette thèse aborde un certain nombre de ces aspects, à travers plusieurs projets :- la caractérisation bioinformatique de transcrits anti-sens produits par des promoteurs bidirectionnels durant le développement thymocytaire- le développement et l'intégration d'un compendium d'interactions géniques de natures diverses (interactions physiques, régulations, etc), ainsi qu'un outil de visualisation de graphes adapté - l'étude d'un système de transdifférentiation de lymphocytes pre-B en macrophages par induction de CEBPa, et la construction d'un modèle de régulation, grâce à l'analyse intégrée de données de puces à ADN, de ChIP-seq et de séquence / One of the fundamental challenges of modern biology is to better understand the mechanisms regulating gene expression, on which the functioning and differentiation of cells depend. In particular, disorders in these mechanisms may be the cause of diseases such as cancer. High throughput technologies of the post-genomic era allow mass production of data including gene expression, binding sites of transcription factors and chromatin state. These data a wealth of information for the study of regulatory mechanisms. However, the amount and heterogeneity of these data raise many bioinformatics issues related to access, visualization, analysis and integration of these.This thesis addresses a number of these aspects, through several projects:- bioinformatics characterization of antisense transcripts produced by bidirectional promoters during thymocyte development,- development and integration of a compendium of gene interactions of various kinds (physical interactions, regulations, etc.), and a graph visualization tool,- the study of a transdifferentiation system of pre-B lymphocytes into macrophages by induction of CEBPa, and the construction of a regulation model, thanks to the integrated analysis of DNA microarrays, ChIP-seq and sequence data.This work provides an illustration of some of the bioinformatics issues related to the exploitation of these data and methodologies to efficiently extract biological information, particularly to answer questions regarding the mechanisms of transcription and its regulation in the hematopoietic system.

The widespread success of data analysis in a growing number of application domains has lead to the development of a variety of purpose build data processing systems. Today, many organizations operate whole fleets of different data related systems. Although this differentiation has good reasons there is also a growing need to create holistic perspectives that cut across the borders of individual systems. Application experts that want to create such perspectives are confronted with a variety of programming interfaces, data formats, and the task to combine available systems in an efficient manner. These issues are generally unrelated to the application domain and require a specialized set of skills. As a consequence, development is slowed down and made more expensive which stifles exploration and innovation. In addition, the direct use of specialized system interfaces can couple application code to specific processing systems. In this dissertation, we propose the data processing platform DataCalc which presents users with a unified application oriented programming interface and which automatically executes this interface in an efficient manner on a variety of processing systems. DataCalc offers a managed environment for data analyses that enables domain experts to concentrate on their application logic and decouples code from specific processing technology. The basis of this managed processing environment are the high-level domain oriented program representation DCIL and a flexible and extensible cost based optimization component. In addition to traditional up-front optimization, the optimizer also supports dynamic re-optimization of partially executed DCIL programs. This enables the system to benefit from dynamic information that only becomes available during execution of queries. DataCalc assigns workloads to available processing systems using a fine grained task scheduling model to enable efficient exploitation of available resources. In the second part of the dissertation we present a prototypical implementation of the DataCalc platform which includes connectors for the relational DBMS PostgreSQL, the document store MongoDB, the graph database Neo4j, and for the custom build PyProc processing system. For the evaluation of this prototype we have implemented an extended application scenario. Our experiments demonstrate that DataCalc is able to find and execute efficient execution strategies that minimize cross system data movement. The system achieves much better results than a naive implementation and it comes close to the performance of a hand-optimized solution. Based on these findings we are confident to conclude that the DataCalc platform architecture provides an excellent environment for cross domain data analysis on a heterogeneous federated processing architecture.