PARAMETER SYNTHESIS FOR BIOCHEMICAL MODELS
Systems Biology models often have numerous parameters, such as kinetic constants, decay rates and drift/diffusion terms, which are unknown or only weakly constrained by existing experimental knowledge. A crucial problem for Systems Biology is that these parameters are often very difficult to measure directly. Furthermore, they may vary greatly according to their in vivo context. As a result, computational methods for the estimation or synthesis of these parameters are of great interest.
The goal of our research is to develop effective, fast, and scalable methods, techniques and tools for automated parameter synthesis for the computational analysis of biological systems.
Digital Bifurcation Analysis of Dynamical Systems
Bifurcation analysis is a central task of the analysis of parameterised
high-dimensional dynamical systems that undergo transitions as parameters are
changed. The classical numerical and analytical methods are typically limited
to a small number of system parameters.
The goal of our research is to develop a novel
approach to bifurcation analysis that is based on a suitable discrete
abstraction of the system and employs model checking for discovering critical
parameter values, referred to as bifurcation points, for which various kinds
of behaviour (equilibrium, cycling) appear or disappear.
Model Discrimination and Selection
When given several models for the same biochemical process, which one is the best in the face of uncertainty about model structure and parameters governing model dynamics? Traditionally, this question has often been approached by model calibration. Our approach is to judge a model superior if there exist parameters (in its usually high-dimensional parameter space) that allow the model to mimic biologically observed behaviour more closely than other models.
The goal of our research is to develop formally sound definitions for model discrimination and to propose algorithmic techniques to automatically select appropriate models from a set of candidate models.
Comprehensive Modelling Platform
CMP is a general framework for public
sharing, annotation, and visualisation of domain-specific biological models. For a selected organism, the framework is instantiated as a
web-based application which allows capturing several aspects of biological
models represented as biochemical reaction networks or ordinary differential
equations. The key feature relies
on mapping kinetic models to a precise textual and a schematic graphical
representation of the related biological knowledge, thereby supporting the
systems biological view of the modelled organism. Besides model repository
and annotation, the platform includes basic model analysis procedures such as
simulation and static analysis.
Currently, two instances E-Photosynthesis [www.e-photosynthesis.org] and
E-Cyanobacterium [www.e-cyanobacterium.org] are under development.