This thesis consists of three parts: The first and second parts focus on long-time asymptotics of macroscopic and kinetic models respectively, while in the third part we connect these regimes using different scaling approaches. (1) Keller–Segel-type aggregation-diffusion equations: We study a Keller–Segel-type model with non-linear power-law diffusion and non-local particle interaction: Does the system admit equilibria? If yes, are they unique? Which solutions converge to them? Can we determine an explicit rate of convergence? To answer these questions, we make use of the special gradient flow structure of the equation and its associated free energy functional for which the overall convexity properties are not known. Special cases of this family of models have been investigated in previous works, and this part of the thesis represents a contribution towards a complete characterisation of the asymptotic behaviour of solutions. (2) Hypocoercivity techniques for a fibre lay-down model: We show existence and uniqueness of a stationary state for a kinetic Fokker-Planck equation modelling the fibre lay-down process in non-woven textile production. Further, we prove convergence to equilibrium with an explicit rate. This part of the thesis is an extension of previous work which considered the case of a stationary conveyor belt. Adding the movement of the belt, the global equilibrium state is not known explicitly and a more general hypocoercivity estimate is needed. Although we focus here on a particular application, this approach can be used for any equation with a similar structure as long as it can be understood as a certain perturbation of a system for which the global Gibbs state is known. (3) Scaling approaches for collective animal behaviour models: We study the multi-scale aspects of self-organised biological aggregations using various scaling techniques. Not many previous studies investigate how the dynamics of the initial models are preserved via these scalings. Firstly, we consider two scaling approaches (parabolic and grazing collision limits) that can be used to reduce a class of non-local kinetic 1D and 2D models to simpler models existing in the literature. Secondly, we investigate how some of the kinetic spatio-temporal patterns are preserved via these scalings using asymptotic preserving numerical methods.

Dans cette thèse, j'étudie des équations aux dérivées partielles qui modélisent des phénomènes biologiques.Dans la première partie, je m'intéresse à une variante des équations de Keller-Segel qui modélise la chimiotaxie des micro-organismes et vise à expliquer la façon dont des colonies bactériennes s'auto-organisent et forment, en fonction de la quantité de nutriments disponibles, différents motifs géométriques. Pour le modèle en question, je construis des solutions et j'étudie leur comportement en temps long. Je montre que certaines solutions explosent en temps fini.Dans la deuxième partie, je m'intéresse au modèle Intègre et tire avec bruit et fuite non-linéaire, une équation de type Fokker-Planck qui décrit l'activité d'un réseau de neurones. J'améliore certaines estimées sur l'existence globale et l'explosion en temps fini et je démontre des résultats pour une variante du modèle avec un délai synaptique : existence globale, comportement en temps long, recherche de solutions périodiques.Dans la troisième partie, je propose une modélisation d'abord stochastique, ensuite déterministe, pour le phénomène d'adaptation des dommages à l'ADN chez les eucaryote. Des simulations numériques sont proposées et commentées. / In this thesis, I study some partial differential equations modelling biological phenomena.In the first part, I am concerned with a variant of the Keller-Segel equations which models chemotaxis in microorganisms and aims at understanding the way they self-organise and form, depending upon the density of nutrients, different geometrical patterns. For this model, I construct solutions and I study their long time behaviour. I show that some solutions blow-up in finite time.In the second part, I study the model Nonlinear Noisy leaky integrate and fire, a Fokker-Planck type equation which describes the activity of a neural network. I upgrade some estimates on global existence and finite time blow-up and I prove results for a variant of the model in which a synaptic delay is added : global existence, long time behaviour, search of periodic solutions.In the third part, I propose a stochastic model, and then a deterministic model, for the phenomenon of adaptation to DNA damage in eukaryotes. Numerical simulations are proposed and discussed.