Andrej Depperschmidt
University of Freiburg
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Featured researches published by Andrej Depperschmidt.
Annals of Applied Probability | 2012
Andrej Depperschmidt; Andreas Greven; Peter Pfaffelhuber
The Fleming-Viot measure-valued diffusion is a Markov process describing the evolution of (allelic) types under mutation, selection and random reproduction. We enrich this process by genealogical relations of individuals so that the random type distribution as well as the genealogical distances in the population evolve stochastically. The state space of this tree-valued enrichment of the Fleming-Viot dynamics with mutation and selection (TFVMS) consists of marked ultrametric measure spaces, equipped with the marked Gromov-weak topology and a suitable notion of polynomials as a separating algebra of test functions. The construction and study of the TFVMS is based on a well-posed martingale problem. For existence, we use approximating finite population models, the tree-valued Moran models, while uniqueness follows from duality to a function-valued process. Path properties of the resulting process carry over from the neutral case due to absolute continuity, given by a new Girsanov-type theorem on marked metric measure spaces. To study the long-time behavior of the process, we use a duality based on ideas from Dawson and Greven [On the effects of migration in spatial Fleming-Viot models with selection and mutation (2011c) Unpublished manuscript] and prove ergodicity of the TFVMS if the Fleming-Viot measure-valued diffusion is ergodic. As a further application, we consider the case of two allelic types and additive selection. For small selection strength, we give an expansion of the Laplace transform of genealogical distances in equilibrium, which is a first step in showing that distances are shorter in the selective case.
Annals of Applied Probability | 2007
Matthias Birkner; Andrej Depperschmidt
We study a discrete time spatial branching system on
Journal of Mathematical Biology | 2013
Andrej Depperschmidt; N. Ketterer; Peter Pfaffelhuber
\mathbb{Z}^d
Electronic Journal of Probability | 2016
Matthias Birkner; Jiří Černý; Andrej Depperschmidt
with logistic-type local regulation at each deme depending on a weighted average of the population in neighboring demes. We show that the system survives for all time with positive probability if the competition term is small enough. For a restricted set of parameter values, we also obtain uniqueness of the nontrivial equilibrium and complete convergence, as well as long-term coexistence in a related two-type model. Along the way we classify the equilibria and their domain of attraction for the corresponding deterministic coupled map lattice on
Electronic Communications in Probability | 2011
Andrej Depperschmidt; Andreas Greven; Peter Pfaffelhuber
\mathbb{Z}^d
Electronic Journal of Probability | 2013
Matthias Birkner; Jiri Cerny; Andrej Depperschmidt; Nina Gantert
.
Stochastic Processes and their Applications | 2010
Andrej Depperschmidt; Peter Pfaffelhuber
We study a model for the translocation of proteins across membranes through a nanopore using a ratcheting mechanism. When the protein enters the nanopore it diffuses in and out of the pore according to a Brownian motion. Moreover, it is bound by ratcheting molecules which hinder the diffusion of the protein out of the nanopore, i.e. the Brownian motion is reflected such that no ratcheting molecule exits the pore. New ratcheting molecules bind at rate γ. Extending our previous approach (Depperschmidt and Pfaffelhuber in Stoch Processes Appl 120:901–925, 2010) we allow the ratcheting molecules to dissociate (at rate δ) from the protein (Model I). We also provide an approximate model (Model II) which assumes a Poisson equilibrium of ratcheting molecules on one side of the current reflection boundary. Using analytical methods and simulations we show that the speeds of both models are approximately the same. Our analytical results on Model II give the speed of translocation by means of a solution of an ordinary differential equation. This speed gives an approximation for the time it takes to translocate a protein of given length.
Electronic Communications in Probability | 2015
Andrej Depperschmidt; Peter Pfaffelhuber; Annika Scheuringer
We consider random walks in dynamic random environments, with an environment generated by the time-reversal of a Markov process from the oriented percolation universality class. If the influence of the random medium on the walk is small in space-time regions where the medium is typical, we obtain a law of large numbers and an averaged central limit theorem for the walk via a regeneration construction under suitable coarse-graining. Such random walks occur naturally as spatial embeddings of ancestral lineages in spatial population models with local regulation. We verify that our assumptions hold for logistic branching random walks when the population density is sufficiently high.
Electronic Journal of Probability | 2013
Andrej Depperschmidt; Andreas Greven; Peter Pfaffelhuber
Archive | 2012
Matthias Birkner; Jiri Cerny; Andrej Depperschmidt; Nina Gantert