Literatura académica sobre el tema "Adaptation (biologie) – Modèles mathématiques"
Crea una cita precisa en los estilos APA, MLA, Chicago, Harvard y otros
Índice
Consulte las listas temáticas de artículos, libros, tesis, actas de conferencias y otras fuentes académicas sobre el tema "Adaptation (biologie) – Modèles mathématiques".
Junto a cada fuente en la lista de referencias hay un botón "Agregar a la bibliografía". Pulsa este botón, y generaremos automáticamente la referencia bibliográfica para la obra elegida en el estilo de cita que necesites: APA, MLA, Harvard, Vancouver, Chicago, etc.
También puede descargar el texto completo de la publicación académica en formato pdf y leer en línea su resumen siempre que esté disponible en los metadatos.
Artículos de revistas sobre el tema "Adaptation (biologie) – Modèles mathématiques"
Feugeas, J. P. "Quand imagerie et modèles mathématiques viennent au secours de la biologie clinique". Bio Tribune Magazine 28, n.º 1 (agosto de 2008): 5. http://dx.doi.org/10.1007/bf03001638.
Texto completoHOCH, T., P. PRADEL y J. AGABRIEL. "Modélisation de la croissance de bovins : évolution des modèles et applications". INRAE Productions Animales 17, n.º 4 (5 de octubre de 2004): 303–14. http://dx.doi.org/10.20870/productions-animales.2004.17.4.3605.
Texto completoTesis sobre el tema "Adaptation (biologie) – Modèles mathématiques"
Chabrol, Olivier. "Modèles et algorithmes pour l'évolution biologique". Thesis, Aix-Marseille, 2017. http://www.theses.fr/2017AIXM0625.
Texto completoIn this thesis, we studied questions about biological evolution by using mathematical models and bio-informatic algorithms. This work is at the intersection of mathematics, computer science and biology.The major question addressed in this thesis is the detection molecular basisof phenotypic convergence. Evolutionary convergence is the process by which independent species develop similar traits. This evolutionary process is strongly related to fundamental questions such as the role of adaptation .After pointing out different biological concepts linked to evolutionary convergence, we proposed a novel approach combining an original measure of the extent to which a site supports a phenotypic convergence to a binary trait. Thismeasure is based on the “convergence level” of a site which is a mathematical expectation under Markov evolutionary model. We proposed a polynomial time algorithm to compute this index. Our algorithm outperformed two previous algorithms in distinguishing simulated convergent sites from non-convergent ones. With the aim to study the evolutionary convergence of continuous traits, like weight and size, we tried to detect change in evolutionary trends of continuous characters along the tree of life. We proposed a novel method based on anasymmetric version of the linear parsimony, for determining the position of the change in trend which minimizes the total evolutionary cost of the tree. By using the approach on two biological datasets, we obtained results consistentwith those given by previous stochastic approaches
Kucharavy, Andrei. "Molecular mechanisms of aneuploidy-mediated stress-resistance". Electronic Thesis or Diss., Paris 6, 2017. https://accesdistant.sorbonne-universite.fr/login?url=https://theses-intra.sorbonne-universite.fr/2017PA066734.pdf.
Texto completoAneuploidy has historically been associated with detrimental phenotypes and diseases, notably cancer and Down Syndrome. However, recent experimental evidence suggests aneuploidy provides adaptation to numerous stressors, including drug resistance, making aneuploidy study critical to biomedical research. However, the molecular mechanisms underlying this process remained elusive until now. This work focused on exploring several approaches to understanding those mechanisms. Frist, we have developed a general mathematical model of organism adaptation to adverse environments. In our model, the adaptation to environments takes place as a trade-off in the space of traits, of which aneuploidy allows a more efficient and rapid sampling. This model was validated on experimental data and used to predict optimal drug combinations targeting heterogeneous populations breast tumor cells. Second, we used the framework of network biology to model biomolecular networks and apply to them results from the graph theory and existing results on weighted graphs from other domains. We were able to predict the distribution of essential genes, lethal genetic interactions and essential evolvable genes - essential genes that can be deleted in the aneuploid background. We were as well able to build a predictive model for inferring most likely pathways underlying the phenotype of large-scale genetic perturbations. Finally, we attempted to explore several possible modes besides dosage effects by which aneuploidy could impact the gene expression regulation. This required a development of an image analysis toolkit that was validated and released for as open-source software
Taing, Cécile. "Dynamique de concentration dans des équations aux dérivées partielles non locales issues de la biologie". Thesis, Sorbonne université, 2018. http://www.theses.fr/2018SORUS077.
Texto completoThis thesis focuses on the dynamics of Dirac mass concentrations in non-local partial differential and integro-differential equations motivated by evolutionary biology. We consider population models structured in phenotypical traits and, taking into account adaptation and mutation phenomena, we aim to describe the selection of the fittest traits in a given environment. The mathematical modeling of these biological problems leads to nonlinear and nonlocal equations, with a small parameter that induces two time-scales. The asymptotic solutions to these equations are population distributions on the traits space and concentrate in Dirac masses located on the dominant traits. In the first part, we study the Dirac mass dynamics in a chemostat model, using a Hamilton-Jacobi formulation. The chemostat model is a system of equations describing the dynamics of consumers and nutrients in a bioreactor. In a second part, we investigate a competition model structured in age and phenotypical traits. By means of an appropriate factorization, we obtain the asymptotic limit of the solution as a decomposition into two profiles, one in age, the other in traits. When mutations are introduced, a Hamilton-Jacobi equation arises and we prove a uniqueness result of the solution to this equation in the framework of viscosity solutions. The last part is devoted to sexual population models. These models under investigation include asymmetric trait heredity or asymmetric trait-dependent fecundity between the parents: each individual inherits mostly its traits from the female
Hass, Vincent. "Modèles individu-centrés en dynamiques adaptatives, comportement asymptotique et équation canonique : le cas des mutations petites et fréquentes". Electronic Thesis or Diss., Université de Lorraine, 2023. http://www.theses.fr/2023LORR0165.
Texto completoAdaptive dynamics theory is a branch of evolutionary biology which studies the links between ecology and evolution. The biological assumptions that define its framework are those of rare and small mutations and large asexual populations. Adaptive dynamics models describe the population at the level of individuals, which are characterised by their phenotypes, and aim to study the influence of heredity, mutation and selection mechanisms on the long term evolution of the population. The success of this theory comes in particular from its ability to provide a description of the long term evolution of the dominant phenotype in the population as a solution to the “Canonical Equation of Adaptive Dynamics” driven by a fitness gradient, where fitness describes the possibility of mutant invasions, and is constructed from ecological parameters. Two main mathematical approaches to the canonical equation have been developed so far: an approach based on PDEs and a stochastic approach. Despite its success, the stochastic approach is criticised by biologists as it is based on a non-realistic assumption of too rare mutations. The goal of this thesis is to correct this biological controversy by proposing more realistic probabilistic models. More precisely, the aim is to investigate mathematically, under a double asymptotic of large population and small mutations, the consequences of a new biological assumption of frequent mutations on the canonical equation. The goal is to determine, from a stochastic individual-based model, the long term behaviour of the mean phenotypic trait of the population. The question we ask is reformulated into a slow-fast asymptotic analysis acting on two eco-evolutionary time scales. A slow scale corresponding to the dynamics of the mean trait, and a fast scale corresponding to the evolutionary dynamics of the centred and dilated distribution of traits. This slow-fast asymptotic analysis is based on averaging techniques. This method requires the identification and characterisation of the asymptotic behaviour of the fast component and that the latter has ergodicity properties. More precisely, the long time behaviour of the fast component is non-classical and corresponds to that of an original measure-valued diffusion which is interpreted as a centered Fleming-Viot process that is characterised as the unique solution of a certain martingale problem. Part of these results is based on a duality relation on this non-classical process and requires moment conditions on the initial data. Using coupling techniques and the correspondence between Moran's particle processes and Kingman's genealogies, we establish that the centered Fleming-Viot process satisfies an ergodicity property with exponential convergence result in total variation. The implementation of averaging methods, inspired by Kurtz, is based on compactness-uniqueness arguments. The idea is to prove the compactness of the laws of the couple made up of the slow component and the occupation measure of the fast component and then to establish a martingale problem for all accumulation points of the family of laws of this couple. The last step is to identify these accumulation points. This method requires in particular the introduction of stopping times to control the moments of the fast component and to prove that they tend to infinity using large deviation arguments, to reduce the problem initially posed on the real line to the torus case in order to prove compactness, to identify the limit of the fast component by adapting an argument based on Dawson duality, to identify the limit of the slow component and then to move from the torus to the real line
Fumey, Julien. "Tempo et mode de l'évolution des populations cavernicoles de l'espèce Astyanax mexicanus". Thesis, Université Paris-Saclay (ComUE), 2016. http://www.theses.fr/2016SACLS528/document.
Texto completoThe fish Astyanax mexicanus is a particularly suitable model for evolutionary biology studies. Indeed, in this species there are several subterranean populations which live in the total and permanent darkness of cave. These cavefish are well adapted to the life in this inhospitable environment and they show several differences with their surface conspecific such as depigmentation, eye loss and behavioral changes. A major unresolved issue is about the relative role of surface fish standing genetic variation and de novo mutations appeared in cavefish populations after their settlement in caves in their phenotypic evolution. In order to examine this issue, accurate estimations of population ages are very important because many new mutations cannot appear and fix in a recent population. In this thesis we aimed to estimate the age of the Pachón cave population which is considered as one of the oldest and most isolated populations. We developed a new method which is based on measures of the distribution of single nucleotide polymorphism within each population and between populations. Our results, as well as reanalyses of published data about mitochondrial haplotypes and microsatellite loci polymorphism suggest that cavefish populations are much more recent than previously thought (several thousand years and not several hundred thousand years). The consequences of a fast tempo of evolution on the mode of evolution of cavefish are also discussed
Collot, Dorian. "Modélisation des dynamiques adaptatives de la levure de boulanger S. cerevisae dans un environnement saisonnier". Thesis, Université Paris-Saclay (ComUE), 2018. http://www.theses.fr/2018SACLS179/document.
Texto completoAdaptation of species to their environment involves combinations of traits, and in particular life history traits, that influence an organism's selective value. To understand the complexity of adaptation, it is appropriate to decipher the contributions of traits to fitness in the presence of different biotic and abiotic environments. In this thesis, I have investigated fitness components when the environment is seasonal, revealing how such components drive the evolutionary dynamics of quantitative traits.My work is based on the mathematical modeling of experimental evolutions in successive batch cultures of Saccharomyces cerevisiae (baker's yeast). The life cycle of this yeast species is of the respiration-fermentation type: (i) in the presence of glucose, it grows by fermentation, transforming glucose into ethanol; (ii) once glucose has been consumed, it grows by respiration, consuming this time ethanol. This sequence corresponds to the two « seasons » in a batch culture and leads to a cycle of successive batches if cells are periodically transferred into fresh medium. By using differential equations for the time courses, my thesis work shows how growth dynamics and environmental features (abiotic or biotic) generate selection pressures on the different traits during these successive seasons, thereby determining evolutionary trajectories.To describe batch dynamics, I first developed and calibrated a set of differential equations describing the growth dynamics of a population of yeast cells throughout a batch, allowing for one or multiple strains to be present (Chapter 1). Based on this model where cells divide without changing genotype, I then showed that a strain's fitness can be understood in terms of just a few components that are easily specified mathematically. I was then able to determine which traits were under selection and how the corresponding selection pressures were affected by the abundances of each strain in the yeast population (Chapter 2). Selected traits were found to be of two types: life history traits associated with growth and mortality rates, and “transition” traits that correspond to the way a strain reacts to environmental change. I also showed that the contributions of the different fitness components are tied to both selected and non-selected traits via the lengths of seasons. Thus, during population dynamics arising across successive batches, these components change, modifying the selection pressure on each trait. One therefore has a feedback loop, revealing why fitness is frequency-dependent in this system.Next, using the fitness decomposition, I studied adaptive dynamics in successive batch cultures. In such a framework where genotypic changes were allowed, and assuming that there was a trade-off between two traits, I showed that adaptive evolutionary dynamics could lead to the emergence of new relations between selected and non-selected traits (Chapter 3).Furthermore, in order to compare my theoretical predictions to experimental results, I used mathematical and statistical models to analyze two datasets (Chapter 4). The first dataset provides trait measurements in “evolved” strains, i.e., strains obtained after evolution across successive batches, as well as of those same traits in the “ancestral” strains at the origin of the experimental evolution. Parameters inference for the different strains showed that selection had operated mainly on ethanol-related traits (production and consumption). A second dataset was obtained from batch experiments putting strains in competition with one another; the analysis showed that my theoretical modeling well predicted the roles of the different traits for determining the relative fitness of the strains
Pellegrin, Xavier. "Oscillations dans des modèles mathématiques issus de la biologie". Paris 7, 2014. http://www.theses.fr/2014PA077263.
Texto completoLn this report, we focus on mathematical analysis of two models coming from biology. The first model, a Kuramoto model, describes the time-evolution of a large number of mean-field coupled phase oscillators. The second one is an original oscillation model, based on a singuiar perturbation of a delayed differential equation. It had been introduced in relation with oscillatory patterns observed in neural networks, and it is subject fo mathematical analysis since the 1980's
Bois, Richard. "Adaptation de maillages anisotropes par un estimateur d'erreur hiérarchique". Thesis, Université Laval, 2012. http://www.theses.ulaval.ca/2012/29273/29273.pdf.
Texto completoIn this thesis, we present a new hierarchical error estimator that can be used in a mesh adaptation algorithm to obtain a more accurate approximation to the solution of a partial differential equation. This error estimator has many advantages that other existing error estimators do not have or lack of. For instance, it is, by construction, independant of the differential operator used to model a certain physical phenomena. It is also naturally generalisable to the case of approximations of arbitrary order, and this, without any specific treatment to the underlying theory. Finally, it is efficient, optimal in a sense that will be defined and permits the elements to stretch in a priviledged direction (anisotropy) in order to obtain high accuracy against regularly refined meshes. Many examples are given in the one, two and three dimensional cases. Analytical examples (the solution is known) is given to measure the effiency and precision of the new error estimator. Other examples of mesh adaptation for equations modeling different physical phenomena like the flow of a fluid around a cylinder, unsteady diffusion and contact between deformable elastic bodies are presented. These examples show that the new error estimator can be used for a wide variety of problems.
Yoccoz, Gilles Nigel. "Le rôle du modèle euclidien d'analyse des données en biologie évolutive". Lyon 1, 1988. http://www.theses.fr/1988LYO10111.
Texto completoWane, Bocar Amadou. "Adaptation de maillages et méthodes itératives avec applications aux écoulements à surfaces libres turbulents". Thesis, Université Laval, 2012. http://www.theses.ulaval.ca/2012/29353/29353.pdf.
Texto completoLibros sobre el tema "Adaptation (biologie) – Modèles mathématiques"
Adaptation in natural and artificial systems: An introductory analysis with applications to biology, control, and artificial intelligence. Cambridge, Mass: MIT Press, 1992.
Buscar texto completoPavé, Alain. Modélisation en biologie et en écologie. Lyon: Aléas, 1994.
Buscar texto completoV, Jean Roger, ed. Une approche mathématique de la biologie. Chicoitimi, Québec: Gaëtan Morin, 1987.
Buscar texto completo1940-, Jean Roger, ed. Une Approche mathématique de la biologie. Chicoutimi, Qué: Morin, 1987.
Buscar texto completoBertrandias, F. Mathématiques pour les sciences de la nature et de la vie. Grenoble: Presses universitaires de Grenoble, 1990.
Buscar texto completoThom, René. Structural stability and morphogenesis: An outline of a general theory of models. Redwood City, Calif: Addison-Wesley, Advanced Book Program, 1989.
Buscar texto completoThom, René. Structural stability and morphogenesis: An outline of a general theory of models. Reading, Mass: Addison-Wesley Pub., 1989.
Buscar texto completoChauvet, Gilbert. Comprendre l'organisation du vivant et son évolution vers la conscience. Paris: Vuibert, 2006.
Buscar texto completoA primer of ecology. Sunderland, Mass: Sinauer Associates, 1995.
Buscar texto completoA primer of ecology. 2a ed. Sunderland, Mass: Sinauer Associates, 1998.
Buscar texto completo