TY  - INPR
A1  - Méléard, Sylvie
A1  - Roelly, Sylvie
T1  - Evolutive two-level population process and large population approximations
N2  - We are interested in modeling the Darwinian evolution of a population described by two levels of biological parameters: individuals characterized by an heritable phenotypic trait submitted to mutation and natural selection and cells in these individuals influencing their ability to consume resources and to reproduce. Our models are rooted in the microscopic description of a random (discrete) population of individuals characterized by one or several adaptive traits and cells characterized by their type. The population is modeled as a stochastic point process whose generator captures the probabilistic dynamics over continuous time of birth, mutation and death for individuals and birth and death for cells. The interaction between individuals (resp. between cells) is described by a competition between individual traits (resp. between cell types). We are looking for tractable large population approximations. By combining various scalings on population size, birth and death rates and mutation step, the single microscopic model is shown to lead to contrasting nonlinear macroscopic limits of different nature: deterministic approximations, in the form of ordinary, integro- or partial differential equations, or probabilistic ones, like stochastic partial differential equations or superprocesses.
T3  - Preprints des Instituts für Mathematik der Universität Potsdam - 2 (2013) 8 
KW  - Two-level interacting process
KW  - birth-death-mutation-competition point process
KW  - non-linear integro-differential equations
Y1  - 2013
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-64604
SN  - 2193-6943
ER  - 
TY  - INPR
A1  - Keller, Peter
A1  - Roelly, Sylvie
A1  - Valleriani, Angelo
T1  - A quasi-random-walk to model a biological transport process
N2  - Transport Molecules play a crucial role for cell viability. Amongst others, linear motors transport cargos along rope-like structures from one location of the cell to another in a stochastic fashion. Thereby each step of the motor, either forwards or backwards, bridges a fixed distance. While moving along the rope the motor can also detach and is lost. We give here a mathematical formalization of such dynamics as a random process which is an extension of Random Walks, to which we add an absorbing state to model the detachment of the motor from the rope. We derive particular properties of such processes that have not been available before. Our results include description of the maximal distance reached from the starting point and the position from which detachment takes place. Finally, we apply our theoretical results to a concrete established model of the transport molecule Kinesin V.
T3  - Preprints des Instituts für Mathematik der Universität Potsdam - 2 (2013) 3 
KW  - Markov chain
KW  - random walk
KW  - molecular motor
KW  - step process
Y1  - 2013
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-63582
ER  -