This thesis is concerned with methodologies for the accurate quantitative modelling of molecular biological systems. The first part is devoted to the chemical Langevin equation (CLE), a stochastic differential equation driven by a multidimensional Wiener process. The CLE is an approximation to the standard discrete Markov jump process model of chemical reaction kinetics. It is valid in the regime where molecular populations are abundant enough to assume their concentrations change continuously, but stochastic fluctuations still play a major role. We observe that the CLE is not a single equation, but a family of equations with shared finite-dimensional distributions. On the theoretical side, we prove that as many Wiener processes are sufficient to formulate the CLE as there are independent variables in the equation, which is just the rank of the stoichiometric matrix. On the practical side, we show that in the case where there are m_1 pairs of reversible reactions and m_2 irreversible reactions, there is another, simple formulation of the CLE with only m_1+m_2 Wiener processes, whereas the standard approach uses 2m_1+m_2. Considerable computational savings are achieved with this latter formulation. A flaw of the CLE model is identified: trajectories may leave the nonnegative orthant with positive probability. The second part addresses the challenge when alternative, structurally different ordinary differential equation models of similar complexity fit the available experimental data equally well. We review optimal experiment design methods for choosing the initial state and structural changes on the biological system to maximally discriminate between the outputs of rival models in terms of L_2-distance. We determine the optimal stimulus (input) profile for externally excitable systems. The numerical implementation relies on sum of squares decompositions and is demonstrated on two rival models of signal processing in starving Dictyostelium amoebae. Such experiments accelerate the perfection of our understanding of biochemical mechanisms.

Traditionally, differential-equation models for population dynamics have considered organisms as "fixed" entities in terms of their behaviour and characteristics. However, there have been many observations of adaptivity in organisms, both at the level of behaviour and as an evolutionary change of traits, in response to the environmental conditions. Taking such adaptiveness into account alters the qualitative dynamics of traditional models and is an important factor to be included, for example, when developing reliable model predictions under changing environmental conditions. In this thesis, we consider piecewise-smooth and smooth dynamical systems to represent adaptive change in a 1 predator-2 prey system. First, we derive a novel piecewise-smooth dynamical system for a predator switching between its preferred and alternative prey type in response to prey abundance. We consider a linear ecological trade-off and discover a novel bifurcation as we change the slope of the trade-off. Second, we reformulate the piecewise-smooth system as two novel 1 predator-2 prey smooth dynamical systems. As opposed to the piecewise-smooth system that includes a discontinuity in the vector fields and assumes that a predator switches its feeding strategy instantaneously, we relax this assumption in these systems and consider continuous change in a predator trait. We use plankton as our reference organism because they serve as an important model system. We compare the model simulations with data from Lake Constance on the German-Swiss-Austrian border and suggest possible mechanistic explanations for cycles in plankton concentrations in spring.

The retina is the ocular tissue responsible for the detection of light. Its extensive demand for oxygen, coupled with a concomitant elevated supply, renders this tissue prone to both hypoxia and hyperoxia. In this thesis, we construct mathematical models of the retina, formulated as systems of reaction-diffusion equations, investigating its oxygen-related dynamics in healthy and diseased states. In the healthy state, we model the oxygen distribution across the human retina, examining the efficacy of the protein neuroglobin in the prevention of hypoxia. It has been suggested that neuroglobin could prevent hypoxia, either by transporting oxygen from regions where it is rich to those where it is poor, or by storing oxygen during periods of diminished supply or increased uptake. Numerical solutions demonstrate that neuroglobin may be effective in preventing or alleviating hypoxia via oxygen transport, but that its capacity for oxygen storage is essentially negligible, whilst asymptotic analysis reveals that, contrary to the prevailing assumption, neuroglobin's oxygen affinity is near optimal for oxygen transport. A further asymptotic analysis justifies the common approximation of a piecewise constant oxygen uptake across the retina, placing existing models upon a stronger theoretical foundation. In the diseased state, we explore the effect of hyperoxia upon the progression of the inherited retinal diseases, known collectively as retinitis pigmentosa. Both numerical solutions and asymptotic analyses show that this mechanism may replicate many of the patterns of retinal degeneration seen in vivo, but that others are inaccessible to it, demonstrating both the strengths and weaknesses of the oxygen toxicity hypothesis. It is shown that the wave speed of hyperoxic degeneration is negatively correlated with the local photoreceptor density, high density regions acting as a barrier to the spread of photoreceptor loss. The effects of capillary degeneration and treatment with antioxidants or trophic factors are also investigated, demonstrating that each has the potential to delay, halt or partially reverse photoreceptor loss. In addition to answering questions that are not accessible to experimental investigation, these models generate a number of experimentally testable predictions, forming the first loop in what has the potential to be a fruitful experimental/modelling cycle.

This thesis is concerned with large-scale systems of Ordinary Differential Equations that model Biomolecular Reaction Networks (BRNs) in Systems and Synthetic Biology. It addresses the strategies of model reduction and decomposition used to overcome the challenges posed by the high dimension and stiffness typical of these models. A number of developments of these strategies are identified, and their implementation on various BRN models is demonstrated. The goal of model reduction is to construct a simplified ODE system to closely approximate a large-scale system. The error estimation problem seeks to quantify the approximation error; this is an example of the trajectory comparison problem. The first part of this thesis applies semi-definite programming (SDP) and dissipativity theory to this problem, producing a single a priori upper bound on the difference between two models in the presence of parameter uncertainty and for a range of initial conditions, for which exhaustive simulation is impractical. The second part of this thesis is concerned with the BRN decomposition problem of expressing a network as an interconnection of subnetworks. A novel framework, called layered decomposition, is introduced and compared with established modular techniques. Fundamental properties of layered decompositions are investigated, providing basic criteria for choosing an appropriate layered decomposition. Further aspects of the layering framework are considered: we illustrate the relationship between decomposition and scale separation by constructing singularly perturbed BRN models using layered decomposition; and we reveal the inter-layer signal propagation structure by decomposing the steady state response to parametric perturbations. Finally, we consider the large-scale SDP problem, where large scale SDP techniques fail to certify a system’s dissipativity. We describe the framework of Structured Storage Functions (SSF), defined where systems admit a cascaded decomposition, and demonstrate a significant resulting speed-up of large-scale dissipativity problems, with applications to the trajectory comparison technique discussed above.

Colorectal cancer (CRC) arises in part from the dysregulation of cellular proliferation, associated with the canonical Wnt pathway, and differentiation, effected by the Notch signalling network. In this thesis, we develop a mathematical model of ordinary differential equations (ODEs) for the coupled interaction of the Notch and Wnt pathways in cells of the human intestinal epithelium. Our central aim is to understand the role of such crosstalk in the genesis and treatment of CRC. An embedding of this model in cells of a simulated colonic tissue enables computational exploration of the cell fate response to spatially inhomogeneous growth cues in the healthy intestinal epithelium. We also examine an alternative, rule-based model from the literature, which employs a simple binary approach to pathway activity, in which the Notch and Wnt pathways are constitutively on or off. Comparison of the two models demonstrates the substantial advantages of the equation-based paradigm, through its delivery of stable and robust cell fate patterning, and its versatility for exploring the multiscale consequences of a variety of subcellular phenomena. Extension of the ODE-based model to include mutant cells facilitates the study of Notch-mediated therapeutic approaches to CRC. We find a marked synergy between the application of γ-secretase inhibitors and Hath1 stabilisers in the treatment of early-stage intestinal polyps. This combined treatment is an efficient means of inducing mitotic arrest in the cell population of the intestinal epithelium through enforced conversion to a secretory phenotype and is highlighted as a viable route for further theoretical, experimental and clinical study.

Cette thèse porte sur le calcul d'une sur-approximation conservative pour les solutions d'équations différentielles ordinaires en présence d'incertitudes et sur son application à l'estimation et l'analyse de systèmes dynamiques à temps continu. L'avantage principal des méthodes et des algorithmes de calculs présentés dans cette thèse est qu'ils apportent une preuve numérique de résultats. Cette thèse est organisée en deux parties. La première partie est consacrée aux outils mathématiques et aux méthodes d'intégration numérique garantie des équations diff érentielles incertaines. Ces méthodes permettent de caractériser de manière garantie l'ensemble des trajectoires d'état engendrées par un système dynamique incertain dont les incertitudes sont naturellement représentées par des intervalles bornés. Dans cette optique, nous avons développé une méthode d'intégration hybride qui donne de meilleurs résultats que les méthodes d'intégration basées sur les modèles de Taylor intervalles. La seconde partie aborde les problèmes de l'identification et de l'observation dans un contexte à erreurs bornées ainsi que le problème d'atteignabilité continue pour la véri cation de propriétés des systèmes dynamiques hybrides. / This thesis addresses the computation of conservative over-approximation of the solutions of uncertain ordinary di erential equations and its application to the estimation and the analysis of uncertain continuous-time dynamical systems. The main feature of the methods and algorithms presented in this thesis is the fact that they are numerically veri ed and hence can be used to obtain numerical proof of properties. This thesis is organized in two parts. The first part is devoted to the mathematical tools and the guaranteed numerical integration methods for uncertain ordinary di erential equations. These methods make it possible to characterize in a guaranteed way all the state trajectories generated by an uncertain dynamical system whose uncertainties are in a natural way described by bounded boxes. Accordingly, we have developed a hybrid integration method which gives better results than the integration methods based on interval Taylor models. The second part is dedicated to the resolution of identi cation and observation issues in a bounded error context. It also deals with continuous reachability computation for the veri cation of the properties of hybrid dynamical systems.

The author presents some generalized Burgers' equations for incompressible and isothermal flow of viscous non-Newtonian fluids based on the Cross model, the Carreau model, and the Power-Law model and some simple assumptions on the flows. The author numerically solves the traveling wave equations for the Cross model, the Carreau model, the Power-Law model by using industrial data. The author proves existence and uniqueness of solutions to the traveling wave equations of each of the three models. The author also provides numerical estimates of the shock thickness as well as maximum strain $\varepsilon_{11}$ for each of the fluids.

Correct modelling of embankment breach formation is essential for an accurate assessment of the associated flood risk. Modelling breach formation due to overflow requires a thorough understanding of the geotechnical processes in unsaturated soils as well as erosion processes under supercritical flow conditions. This thesis describes 1D slope stability analysis performed for unsaturated soils whose moisture content changes with time. The analysis performed shows that sediment-laden gravity flows play an important role in the erosion behaviour of embankments. The thesis also describes a practical, fast breach model based on a simplified description of the physical processes that can be used in modelling and decision support frameworks for flooding. To predict the breach hydrograph, the rapid model distinguishes between breach formation due to headcut erosion and surface erosion in the case of failure due to overflow. The model also predicts the breach hydrograph in the case of failure due to piping. The assumptions with respect to breach flow modelling are reviewed, and result in a new set of breadth-integrated Navier-Stokes equations, that account for wall shear stresses and a variable breadth geometry. The vertical 2D flow field described by the equations can be used to calculate accurately the stresses on the embankment during the early stages of breach formation. Pressure-correction methods are given for solving the 2D Navier-Stokes equations for a variable breadth, and good agreement is found when validating the flow model against analytical solutions.

L'objet de cette thèse concerne la proposition de modèles paramétriques des processus de branchement uni et multi-types. Nous mettons en valeur l’intérêt de la théorie des processus de branchement et du développement nécessaire des différents outils et de concepts propres à plusieurs domaines. Pour cela, nous commençons par rappeler quelques définitions et résultats de la théorie des processus de branchement uni et multi-types, et ce en temps discret comme en temps continu. On se consacre par la suite au développement méthodologique de ces modèles.Dans la deuxième partie de ce mémoire, nous étudions seulement l'évolution d’une seule population en temps continu, et présentons quelques familles de lois paramétriques, associées à des processus de branchement homogènes particuliers. Des méthodes récursives de calcul, ainsi que des propriétés pertinentes, concernant ces distributions de probabilité, sont dérivées des fonctions génératrices satisfaisant certaines équations aux dérivées partielles linéaires précisés. Les familles proposées seront utiles à la modélisation de systèmes plus cohérents en dynamique de populations, puisqu'on y montre que les hypothèses usuelles de distributions de Poisson ne peuvent être argumentées.Dans la troisième partie, nous étudions le comportement de l'évolution de plusieurs populations en interactions. Nous y présentons aussi des modèles paramétriques de lois, associés à des processus de branchement multi-types en temps continu et homogènes en temps. Nous considérons ensuite un modèle particulier, où une population ``mère donneuse" autonome alimente en individus K populations filles, qui sont, elles, en interaction. Ce modèle est bien adapté à l'étude des systèmes dynamiques des populations en interaction qui reste à la fois simple, mais riche en variétés de comportement. L'étude du système multi-types se fait via l'évolution des fonctions génératrices de la loi multidimensionnelles des effectifs. Pour cela, utilisant les équations différentielles ordinaires et aux dérivées partielles, nous établissons les équations implicites des distributions temporelles et multidimensionnelles, et discutons des méthodes analytiques ou numériques de leur résolution. Nous développons ensuite des exemples de modèles et en particulier celui concernant 3 et 4 populations.En conclusion, nous argumentons la pertinence de cette approche, et l’interprétation des paramètres, qui sont d'un grand intérêt pour le développement de méthodes d'inférence statistique, pour de nombreux domaines d'applications. / This thesis aims to propose parametric models for single and multi-type branching processes. The importance of the theory of branching processes is pointed out. Hence, developing various tools and specific concepts in several domains is important for applications. For those purpose, we recall some definitions and results of the single-and-multi-type branching processes theory in discrete and continuous case. Afterward, we focus on the methodological development of those models.In the second part, the evolution of a single population in the continuous case has been studied. Then, some parametric distribution families associated to particular branching mechanisms are explored. Recursive computational procedure and relevant properties concerning the associted probability distributions are derived from generating functions that satisfy specified linear partial differential equations. The suggested families are useful for the modeling of systems that are more coherent with population dynamics, contrarily to the usual hypothesis of Poisson distributions, that cannot be argued.In the third part, the evolution of different populations with interaction is explored. Similarly, some parametric models of homogeneous multi-type branching processes in continuous time are proposed. Afterwards, we consider a particular model where an autonomous donor parent population feeds in individuals, K types progeny populations that interacts. This model is well adapted to the study of dynamical systems of populations in interaction. This simple model, but has a rich variety of behaviors.The study of such systems is also done regarding the evolution of generating functions of multidimensional ndividual countrings. To achievea such study, ordinary and partial differential equations are used to establish the implicit equations of temporal and multidimensional distributions. Analytical and numerical methods for equation resolution are then discussed, and examples of particular models are developed.In conclusion, the relevancy of this approach is argumed, censidering parameters interpretation in the development of inference methods for the various applied domains.

Tuberkulose ist auch heute noch eine der bedrohlichsten Infektionskrankheiten weltweit, verantwortlich für über 1.5 Millionen Todesfälle jährlich. Diese „Erfolgsgeschichte“ ihres Erregers Mycobacterium tuberculosis ist dabei wesentlich durch einen extrem flexiblen Stoffwechsel bestimmt, der dem Bakterium das Wachstum unter den restriktiven Bedingungen der menschlichen Wirtszelle erlaubt. Diese Arbeit erkundet die Flexibilität des zentralen Kohlenstoffmetabolismus in Mykobakterien mit Hilfe mathematischer Modellierungsansätze, ergänzt durch die Integration von qualitativ hochwertigen experimentellen Daten. Ausgehend von einem Überblick über die metabolische Landschaft des zentralen Kohlenstoffmetabolismus, erhöht sich Schritt für Schritt die Detailtiefe bis hin zur genauen Analyse spezieller infektionsrelevanter metabolischer Wege. Die Verknüpfung des zentralen Kohlenstoffmetabolismus zu umgebenden Stoffwechsel- und Biosynthesewegen wird systematisch offen gelegt, als Voraussetzung für eine thermodynamische Charakterisierung des Systems, welche die Glykolyse als limitierenden Stoffwechselweg unter verschiedenen Wachstumsbedingungen charakterisiert. Basierend auf Protein- und Metabolitdaten im Fleißgleichgewicht, erlaubt eine neu vorgestellte Methode die Vorhersage regulatorischer Punkte für den metabolischen Übergang zwischen verschiedenen Kohlenstoffquellen. Abschließend wird mit Hilfe thermodynamisch-kinetischer Modellierung das Zusammenspiel zweier Stoffwechselwege mechanistisch erklärt, welche den robusten Abbau einer intrazellulären Kohlenstoffquelle ermöglichen. Durch die Entwicklung neuer Modellierungstechniken in Kombination mit hochauflösenden experimentellen Daten, trägt diese Arbeit zum besseren Verständnis der kontextabhängigen Flexibilität des mycobakteriellen Stoffwechsels bei, einem vielversprechenden Angriffspunkt für die Entwicklung neuer Medikamente gegen Tuberkulose. / Tuberculosis remains one of the major global health threats responsible for over 1.5 million deaths each year. This ’success story’ of the causative agent Mycobacterium tuberculosis is thereby closely linked to a flexible metabolism, allowing growth despite the restrictive conditions within the human host. In this thesis, the flexibility of the mycobacterial central carbon metabolism is explored by modeling approaches integrating high-quality experimental data. The analyses zoom in from a network based view to the detailed functionalities of individual, virulence relevant pathways. The interconnection of the central carbon metabolism to the remaining metabolic network is charted as a prerequisite to characterize its thermodynamic landscape, debunking glycolysis as bottleneck in different nutritional conditions. Based on steady state metabolomics and proteomics data, regulatory sites for the metabolic transition between different carbon sources are predicted by a novel method. Finally, the flexible interplay between two seemingly redundant pathways for the catabolism of an in vivo-like carbon source is explained mechanistically by means of thermodynamic-kinetic modeling. By employing novel modeling methods in combination with high-resolution experimental data, this work adds to the mechanistic understanding of the context dependent flexibility of mycobacterial metabolism, an important target for the development of novel drugs in the battle against tuberculosis.