Dans ce travail de thèse, nous avons étudié la variabilité (ou stochasticité) de l’expression des gènes en considérant que le signal stochastique que produit cette expression est porteur d’information quant au processus d’expression lui-même. Cette stochasticité de l’expression génique peut être caractérisée par la variation observée du nombre de protéines produites soit entre différentes cellules isogéniques (portant le même génome) à un instant donné, soit au sein d’une même cellule au cours du temps. Dans un premier temps, nous avons montré expérimentalement que le niveau de stochas- ticité de l’expression d’un gène change suivant son locus (sa position sur le génome). De plus, nous avons montré que, à locus constant, le niveau de stochasticité peut être influencé par des agents modificateurs globaux de l’état chromatinien. Ensuite, nous avons analysé comment la dynamique chromatinienne peut influencer la stochasticité de l’expression génique d’un gène. Pour ce faire, nous avons utilisé une ap- proche de modélisation et simulation que nous avons ensuite confrontée à des données biologiques. L’utilisation d’un modèle à deux états nous a permis de montrer que l’acti- vité du promoteur est caractérisée par de longues périodes durant lesquelles la chromatine empêche la transcription, entrecoupées par de brèves périodes où la transcription est à nouveau rendue possible sous forme de « bursts » de forte intensité. Pour finir, nous avons identifié, par des approches statistiques et par l’utilisation de bases de données génomiques, des éléments caractéristiques de la séquence génomique qui, lors- qu’ils sont présents dans le voisinage d’un gène, peuvent influer sur la stochasticité de celui-ci. Nous avons en particulier montré que, lorsque le gène rapporteur est inséré à proximité d’un autre gène, sa stochasticité augmente de manière significative. Ce travail nous a permis de mettre en évidence un lien entre la dynamique chromatinienne, l’environnement génomique et la stochasticité de l’expression génique. Ce lien offre à la cellule des perspectives évolutives en lui permettant de réguler cette stochasticité, ouvrant ainsi la porte à la sélection d’un niveau approprié de variabilité. / During my PhD, we have studied the variability (or stochasticity) of gene expression assuming that the stochastic signal it produces carries information about the process of gene expression itself. The stochasticity of gene expression can be characterized by the observed variation in the number of proteins produced either by different isogenic cells (cells that have the same genome) at a given time or within a single cell over time. First, we showed experimentally that the level of stochasticity of a gene changes according to its locus (its position on the genome). We have also shown that, for a given locus, the level of stochasticity could be influenced by global chromatin-state modifier agents. Then, we analyzed how the chromatin dynamics can influence the stochasticity of gene expression. This analysis was conducted by using a modeling and simulation approach, the results of which being in turn compared to biological data. Using a two-states model allowed me to show that the activity of a promoter is characterized by long periods during which the chromatin prevents transcription, interspersed by brief periods when transcription can occur in the form of intense bursts. Finally, we identified characteristic genomic elements that, when in the neighbourhood of a gene, may influence its level of stochasticity. In particular, we have shown that when the reporter gene is integrated close to a neighbour gene, its stochasticity is significantly increased. This work allowed me to unravel a link between the chromatin dynamics, the genomic environment and the stochasticity of gene expression. This link confers evolutionary pers- pectives to the cell by allowing it to regulate stochasticity, which allows for the selection of an appropriate level of stochasticity.

<p>Biodiversity in forests depends on long canopy continuity and existence of different elements which function as substrates for varying organisms. Bryophytes often occupy specific substrates with a patchy distribution. The aim of this thesis was to increase the ecological knowledge about two threatened moss species; <i>Buxbaumia viridis</i>, inhabiting decaying wood, and <i>Neckera pennata</i>, inhabiting bark of base-rich deciduous trees. </p><p>Establishment from spores was investigated in <i>Buxbaumia viridis</i> and <i>Neckera pennata</i> and models were created to predict germination of spores as a function of pH and water potential. The effects of pH, phosphorus and nitrogen concentration were studied in <i>Buxbaumia viridis</i>, both on spore germination and on sporophyte occurrences in the field. Colony growth in relation to precipitation and microhabitat variables was studied in <i>Neckera pennata</i>, and a model was used to predict growth of colonies over time. Metapopulation dynamics of <i>Buxbaumia viridis</i> were analyzed as an effect of precipitation, habitat quality and patch quantity. A spatial explicit patch occupancy model was constructed to simulate metapopulation sizes and extinction risk over 100 years.</p><p>The quality of the substrate was very important for spore establishment. Germination success increased with increasing pH in both species. <i>Buxbaumia viridis</i> was less sensitive to low pH than <i>Neckera pennata</i> when water was freely available. However, there was a strong interaction between pH and water potential in prediction of the final cumulative germination: the spores reacted positively to one factor only when the other factor was in a favourable range.</p><p>Precipitation, moisture holding capacity and interference competition were the main factors affecting colony growth of <i>Neckera pennata</i>. <i>Buxbaumia viridis</i> showed large fluctuations in number of occupied patches among years. Both colonizations and extinctions were highly related to precipitation. Spore germination and sporophyte occurrences in the field were positively related to phosphorus concentration and pH of the substrate.</p>

Biodiversity in forests depends on long canopy continuity and existence of different elements which function as substrates for varying organisms. Bryophytes often occupy specific substrates with a patchy distribution. The aim of this thesis was to increase the ecological knowledge about two threatened moss species; Buxbaumia viridis, inhabiting decaying wood, and Neckera pennata, inhabiting bark of base-rich deciduous trees. Establishment from spores was investigated in Buxbaumia viridis and Neckera pennata and models were created to predict germination of spores as a function of pH and water potential. The effects of pH, phosphorus and nitrogen concentration were studied in Buxbaumia viridis, both on spore germination and on sporophyte occurrences in the field. Colony growth in relation to precipitation and microhabitat variables was studied in Neckera pennata, and a model was used to predict growth of colonies over time. Metapopulation dynamics of Buxbaumia viridis were analyzed as an effect of precipitation, habitat quality and patch quantity. A spatial explicit patch occupancy model was constructed to simulate metapopulation sizes and extinction risk over 100 years. The quality of the substrate was very important for spore establishment. Germination success increased with increasing pH in both species. Buxbaumia viridis was less sensitive to low pH than Neckera pennata when water was freely available. However, there was a strong interaction between pH and water potential in prediction of the final cumulative germination: the spores reacted positively to one factor only when the other factor was in a favourable range. Precipitation, moisture holding capacity and interference competition were the main factors affecting colony growth of Neckera pennata. Buxbaumia viridis showed large fluctuations in number of occupied patches among years. Both colonizations and extinctions were highly related to precipitation. Spore germination and sporophyte occurrences in the field were positively related to phosphorus concentration and pH of the substrate.

Human upright posture exhibits an everlasting oscillatory behavior of complex nature, called as human postural sway. Variations in the position of the Center-of-Pressure (CoP) were used to describe the human postural sway. In this study / CoP data, which has experimentally been collected from 28 different subjects (14 males and 14 females with their ages ranging from 6 to 84), who were divided into 4 groups according to their ages has been analyzed. The data collection from each of the subjects was performed in 5 successive trials, each of which has lasted for 180-seconds long. Linear analysis methods such as the variance/standard deviation, Fast Fouri&eacute / r Transformation, and Power Spectral Density estimates were applied to the detrended CoP signal of human postural sway. Also the Run test and Ensemble averages methods were used to search for stationarity and ergodicity of the CoP signal respectively. Furthermore, in order to reveal the nonlinear characteristics of the human postural sway, its dynamics were reconstructed in m-dimensional state space from the CoPx signals. Then, the correlation dimension (D2) estimates from the embedded dynamics were calculated. Additionally, the statistical and dynamical measures computed were checked against any significant changes, which may occur during aging. The results of the study suggested that human postural sway is a stationary process when 180-second long biped quiet stance data is considered. In addition, it exhibits variable dynamical structure complex in nature (112 deterministic chaos versus 28 stochastic time series of human postural sway) for five successive trials of 28 different subjects. Moreover, we found that groups were significantly different in the correlation dimension (D2) measure (p&amp / #8804 / 0.0003). Finally, the behavior of the experimental CoPx signals was checked against two types of linear processes by using surrogate data method. The shuffled CoPx signals (Surrogate I) suggested that temporal order of CoPx is important / however, phase-randomization (Surrogate II) did not change the behavioral characteristics of the CoPx signal.

La prise de décision cellulaire se traduit par la capacité de toute cellule vivante à intégrer les différentes informations provenant de son environnement, et à les transformer en une réponse biologique cohérente. Il est aujourd'hui de plus en plus démontré que les populations cellulaires présentent une hétérogénéité quantitative et qualitative significative, qui pourrait jouer un rôle essentiel dans le fonctionnement des organismes vivants. La première partie de ma thèse a ainsi consisté à étudier la variabilité de l'expression génique au cours de la différenciation de progéniteurs érythrocytaires aviaires primaires, à l'échelle de la cellule unique. L'expression de 92 gènes a été analysée par RT-qPCR dans des cellules isolées à différents temps de différenciation. Les principaux résultats de cette étude ont montré que la variabilité de l'expression des gènes, mesurée par l'entropie de Shannon, atteint un niveau maximal à 8h-24h de différenciation, simultanément à une chute du nombre de gènes corrélés. Cette augmentation de la variabilité génique précède l'engagement irréversible des cellules dans le processus de différenciation érythrocytaire identifié entre 24 et 48h. Cette étude a également mis en lumière le gène LDHA (Lactate dehydrogenase A), codant pour une enzyme de la glycolyse anaérobie, dans les progéniteurs érythrocytaires en état d'auto-renouvellement et aux points critiques, 8h et 24h, de la différenciation. La deuxième partie de ma thèse a donc consisté à analyser le rôle précis de LDHA dans l'auto-renouvellement des progéniteurs érythrocytaires, ainsi que les variations du métabolisme du glucose au cours de la différenciation. Nos premiers résultats suggèrent que le processus de différenciation érythrocytaire s'accompagne d'un changement métabolique correspondant au passage de la glycolyse anaérobie dépendante de LDHA, vers une production d'énergie aérobie, reposant sur la phosphorylation oxydative / The meaning of cell decision making consists in the capacity of every living cell to integrate environmental information and to transform it in a coherent biological response. Nowadays it is increasingly demonstrated that cell populations present a significant quantitative and qualitative heterogeneity that could be involved in living organisms functions. Thus, the first part of my thesis consisted in studying gene expression variability at the single-cell level during the differentiation process of primary avian erythroid progenitor cells. The expression of 92 genes was analyzed using RT-qPCR in cells isolated at different differentiation time-points. The main results of this study showed that gene expression variability, as measured by Shannon entropy, reached a maximal level, simultaneously to a drop in the number of correlated genes, at 8-24h of differentiation. This increase of the gene expression variability preceded the irreversible commitment of cells into differentiation, identified between 24h and 48h. This analysis also highlighted the potential importance ofLDHA(Lactate dehydrogenase A) encoding a glycolytic enzyme, in erythroid progenitors self-renewal and at the critical differentiation time-point 8-24h. Therefore the second part of my thesis consisted in analyzing the role of LDHA in erythroid progenitors self-renewal and the variations of glucose metabolism during the differentiation process. Our first results suggested that erythroid differentiation might be accompanied with a metabolic change, corresponding to a switch from anaerobic glycolysisdepending upon LDHA, toward aerobic energy production, relying upon oxidative phosphorylation

La presente tesis doctoral, se centra en el desarrollo de métodos matemáticos para el estudio de procesos estocásticos de interés en física y otras ciencias naturales. Fundamentalmente se consideran sistemas de particulas en interacción, prestando especial atención al efecto de la heterogeneidad entre los componentes del sistema, así como el retraso en las interacciones. También se estudian propiedades de sincronización en sistemas de elemenentos excitables no identicos. Se desarrollan diversos métodos analíticos para estudiar este tipo de sistemas y se derivan diversos resultados mátematicos, algunos exactos y otros aproximados, relevantes para el entendimiento general de este tipo de sitemas. Los métodos desarrollados son aplicados al estudio de diversos sistemas concretos, de interés en expresión genética, epidemiología o economía.

This dissertation focuses on selected aspects of network congestion arising in liberalized electricity markets and their management methods with a special weight placed on the integration of increased renewable generation in Europe and Germany. In a first step, the theoretical concepts of congestion management are introduced complemented by a review of current management regimes in selected countries. In the second step, the European approach of managing congestion on international as well as national transmission links is analyzed and the benefits of an integrated congestion management regime are quantified. It is concluded that benefits can be achieved by a closer cooperation of national transmission system operators (TSOs). Thirdly, the German congestion management regime is investigated and the impact of higher renewable generation up to 2020 on congestion management cost is determined. It is shown that a homogeneous and jointly development of generation and transmission infrastructure is a prerequisite for the application of congestion alleviation methods and once they diverge congestion management cost tend to increase substantially. Lastly, the impact of intermittent and uncertain wind generation on electricity markets is analyzed. A stochastic electricity market model is described, which replicates the daily subsequent clearing of reserve, dayahead, and intraday market typical for European countries, and numerical results are presented.

This dissertation focuses on selected aspects of network congestion arising in liberalized electricity markets and their management methods with a special weight placed on the integration of increased renewable generation in Europe and Germany. In a first step, the theoretical concepts of congestion management are introduced complemented by a review of current management regimes in selected countries. In the second step, the European approach of managing congestion on international as well as national transmission links is analyzed and the benefits of an integrated congestion management regime are quantified. It is concluded that benefits can be achieved by a closer cooperation of national transmission system operators (TSOs). Thirdly, the German congestion management regime is investigated and the impact of higher renewable generation up to 2020 on congestion management cost is determined. It is shown that a homogeneous and jointly development of generation and transmission infrastructure is a prerequisite for the application of congestion alleviation methods and once they diverge congestion management cost tend to increase substantially. Lastly, the impact of intermittent and uncertain wind generation on electricity markets is analyzed. A stochastic electricity market model is described, which replicates the daily subsequent clearing of reserve, dayahead, and intraday market typical for European countries, and numerical results are presented.

Complexity science has come into the limelight in recent years as the scientific community begins to grapple with higher-order natural phenomena that cannot be fully explained via the behaviour of components at lower levels of organization. Network modeling and analysis, being a powerful tool that can capture the interconnections that embody complex behaviour, has therefore been at the forefront of complexity science. In ecology, the network paradigm is relatively young and there remain limitations in many ecological network studies, such as modeling only one type of species interaction at a time, lack of realistic network structure, or non-inclusion of community dynamics and environmental stochasticity. I introduce bioenergetic network models that bring together for the first time many of the fundamental structures and mechanisms of species interactions present in real ecological communities. I then use these models to address some outstanding questions that are relevant to understanding ecological networks at the systems level rather than at the level of subsets of interactions. Firstly, I find that realistic red-shifted environmental noise, and synchrony of species responses to noise, are associated with increased variability in ecosystem properties, with implications for predictive ecological modeling which usually assumes white noise. Next, I look at simultaneous species extinction and invasion, finding that as their individual impacts increase, their combined impact becomes decreasingly additive. In addition, the greater the impact of extinction or invasion, the lesser their reversibility via reintroduction or eradication of the species in question. For modifications of pairwise species interactions by third-party species, a phenomenon that has so far been studied one interaction at a time, I find that the many interaction modifications that occur concurrently in a community can collectively have systematic effects on total biomass and species evenness. Finally, examining a higher level of organization in the form of compartmentalized networks, I find that the relationship between intercompartment connectivity and the impacts of species decline depends considerably on network topology and whether the consumer-resource functional response is prey- or ratio-dependent. Overall, the results vary considerably across model communities with different parameterizations, underscoring the contingency and context dependence of nature that scientists and policy makers alike should no longer ignore. This work hopes to contribute to a growing multidisciplinary understanding, appreciation and management of complex systems that is fundamentally transforming the modern world and giving us insights on how to live more harmoniously within our environment.

Bien que largement étudiés, les mécanismes fondamentaux de prise de décision dans les processus de différenciation cellulaire restent mal compris. Les théories déterministes, souvent basées sur des études populationnelles, atteignent rapidement leur limite lorsqu’il s’agit d’expliquer les différences de choix individuels de cellules, pourtant exposées au même environnement. L’objectif de ma thèse est donc d’étudier les premières étapes de la différenciation des cellules hématopoïétiques à l’échelle de la cellule unique, par des analyses transcriptomiques, protéomiques et morphologiques. Ce travail a été effectué sur deux modèles de différenciation : les lymphocytes T régulateurs et les cellules CD34+ humaines issues de sang de cordon. Nous avons observé le comportement de ces cellules uniques après stimulation. Grâce à la combinaison de la microscopie en time lapse et des analyses moléculaires réalisées à l’échelle de la cellule individuelle, nous avons pu démontrer que le choix du devenir cellulaire n’était pas unique, programmé. La cellule passe d’abord par un état dit « multi-primed », métastable où elle exprime des gènes de plusieurs lignées différentes, puis elle passe par une phase dite « incertaine », instable où elle hésite entre deux phénotypes avant de se stabiliser dans un état fixe. Nos observations sont cohérentes avec une explication stochastique de la prise de décision. La différenciation serait donc un processus spontané, dynamique, fluctuant et non un processus prédéterminé. Les décisions du destin cellulaire sont prises séparément par les cellules individuelles. / Despite intensively studies, the fundamental mechanisms of cell fate decision during cellular differentiation still remain unclear. The deterministic mechanisms, often based on studies of large cell populations, cannot explain the difference between individual cell fates choices placed in the same environment. The aim of my thesis work is to study the first steps of hematopoietic cell differentiation at the single cell level thanks to transcriptomic, proteomic and morphological analyses. Two differentiation models have been used: T regulatory lymphocytes and human cord blood-derived CD34+ cells. The behavior of individual cells following stimulation has been analyzed. Using time-lapse microscopy coupled to single cell molecular analyses, we could demonstrate that the cell fate choice is not a unique, programmed event. First, the cell reaches a metastable “multi-primed” state, which is characterized by a mixed lineage gene expression pattern. After transition through an “uncertain”, unstable state, characterized by fluctuations between two phenotypes, the cell reaches a stable state. Our observations are coherent with a stochastic model of cell fate decision. The differentiation is likely to be a spontaneous, dynamic, fluctuating and not a deterministic process. The cell fate decisions are taken by individual cells.