This course has been developed in collaboration with Professor Monika Heiner and her team at the Computer Science Department, Brandenburg University of Technology, Cottbus, Germany
In this course we will show how to develop approaches to support the modelling of large and complex biological systems by the use of a novel integrative combination of hierarchy and colour in Petri nets, which promises to be particularly helpful in investigating spatial aspects of biochemical network behaviour, such as communication at the intra- and inter-cellular levels.
Tutorial level: Medium to advanced
Prior knowledge required: Suitable for biochemists with an understanding of biochemical networks, and enzyme kinetics, as well as for computer scientists and engineers familiar with basic modelling approaches.
In this tutorial we show how biochemical networks can be modelled in a modular fashion, using both a qualitative approach -- Qualitative Petri nets, and quantitative approaches -- Continuous Petri nets and Stochastic Petri nets. We review the major elementary building blocks of a cellular signalling model, discuss which critical design decisions have to be made during model building, and present a number of novel computational tools that can help to explore alternative modular models in an easy and intuitive manner. These tools, which are based on Petri net theory, offer convenient ways of composing models, and permit a qualitative analysis of their behaviour.
We will illustrate our approach using a generic model of a signalling cascade, and then relate this to existing models of the MAPK pathway, e.g. Levchenko, Brown and Schoerbel. We will show how the dynamic behaviour of such a pathway is related to its modular structure, and explore the use of stochastic versus deterministic techniques to generate behaviour traces. We will also introduce the use of temporal logic model checking of the pathway to characterise behavioural properties.
We will also introduce the area of Multiscale modelling which addresses the challenge of modelling and analysing complex biological systems at multiple scales (spatial and temporal). We illustrate our approach with case studies demonstrating hierarchical flattening, treatment of space, and hierarchical organisation of space.
Finally, we will show how our approaches can be applied to support the design and construction process in Synthetic Biology, and illustrate this with some examples from our research.
The ultimate aim is to introduce a general approach that provides the foundations for a structured formal engineering of large-scale models of biochemical networks.
We will illustrate the construction of the models in Petri nets using the suite of Snoopy and related tools, from the Brandenburg University of Technology Cottbus. Snoopy supports qualitative as well as quantitative Petri nets, including continuous and stochastic Petri nets and their simulation. Snoopy's export feature permits interfacing to various analysis tools devoted to standard Petri net theory, as well as a variety of model checkers, permitting more detailed evaluations of qualitative, continuous and stochastic Petri nets.
Centre for Systems and Synthetic Biology
in London, UK
is strengthening its activities in Bioinformatics, Systems Biology and
There are several open positions for talented and able academics, postdoctoral researchers and PhD students in the area of Systems and Synthetic Biology at Brunel.
For more details, contact Professor David Gilbert or Professor Nigel Saunders. David will be available at the tutorial to talk about research opportunities at Brunel.
The work presented in this tutorial has been partially funded by