Research Assistant, PhD student
Institute for Systems Theory and Automatic Control
University of Stuttgart
Office: Room 3.238
Phone: +49 711 685 -69912
Fax: +49 711 685 -67735
Email: daniella.schittler(at) ist.uni-stuttgart.de
Systems biology: Mathematical modeling of cell type transitions
The aim of my research is to develop mathematical modeling frameworks
to quantitatively study cell biological systems and data,
in particular the problem of cell type transitions.
For this purpose, we make use of tools from, e.g., systems and control theory, nonlinear dynamics, mathematical analysis, and simulation technology.
The development of models comprises three different levels that play an important role in cell type transitions,
as well as interfaces between these different levels:
- Genetic switch models: We apply systems-theoretic tools such as
multistability and bifurcation analysis to study the dynamic behavior
of the genetic switch system.
Furthermore, we use these models for
simulations as well as extensions to stochastic model versions in order to elucidate system properties.
[Schittler et al., Chaos 2010]
- Gene regulatory network (GRN) models:
Dynamical models of GRNs are fitted to data from our experimental partners in
interdisciplinary projects, e.g.,
to understand and control the differentiation of mesenchymal stem cells into bone or
cartilage cells for tissue engineering and therapeutic use.
We have recently developed a method
[Schittler et al., to appear Proc. ECC 2013]
that allows to construct fashion
a high-dimensional GRN model which exhibits
the same multistability properties as a given, low-dimensional genetic switch model.
At the same time, the obtained GRN model fulfills the required network structure
that can, for example, be deduced from qualitative knowledge about the biological system.
- Cell population models:
Proliferating cell populations are commonly studied via labeling techniques (such as CFSE or BrdU). For these systems, we have developed
generalized model classes, that on the one hand incorporate the crucial properties of both the observable label intensity, and on the other hand of the cell population.
Thereby, our model class contains existing models as special cases, but importantly
enables novel solution strategies:
Although yielding a system of PDEs,
we show that these models can be decomposed into
an ODE system and a set of analytical expressions, which makes them amenable to
as well as efficient numerical simulations.
Schittler et al., WCSB 2011 ;
Schittler et al., WCSB 2012
; Schittler et al., to appear BMC Sys. Biol. (Suppl.) 2013]
We use population balance equations to study which types of dynamics in an underlying
genetic switch may cause certain dynamics regarding cell type transitions
on the population level.