Computational modelling & Systems Biology

Computational modelling and analysis of biochemical networks contribute to a better understanding of biological systems by

  • explaining behaviours and mechanisms, and
  • predicting the behaviour of a system under different conditions.

Such approaches are at the core of Systems Biology, which attempts to understand biological systems by modelling the interaction of their components, and is a crucial discipline in the life sciences.

Multiscale modelling

Multiscale modeling is the field of solving physical problems which have important features at multiple scales, particularly multiple spatial and/or temporal scales. In this project we focussed on spatial aspects, with an application to biological systems.

We developed 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 intercellular levels.

Petri nets

Petri nets are a natural and established notation for describing reaction networks.

  • They can easily represent reactions and biochemical components.
  • They are particularly attractive to biologists. The intuitive visualization is a consequence of the executable graphical formalism.
  • They have a formal semantics.
  • They provide a unifying framework which permits to move easily between the qualitative, stochastic and continuous modelling paradigms.
  • There is a rich set of sophisticated analysis techniques, which are supported by reliable tools. Tools used in this project.

A drawback of previous modelling approaches, including Petri nets, is their limitation to relatively small networks. Biological systems can be represented as networks which themselves typically contain regular (network) structures, and/or repeated occurrences of network patterns. Moreover, this organisation occurs in a hierarchical manner, reflecting the physical and spatial organisation of the organism, from the intracellular to the intercellular level and beyond (tissues, organs etc.).

Advanced Petri net concepts

There are two orthogonal concepts which can be used to structure Petri net models.

  • Hierarchical Petri Nets reuse the well-established engineering principle of hierarchical decomposition to manage the design of large-scale systems. Sub-networks are hidden as building blocks within macro nodes.
  • Coloured Petri Nets reuse (discrete) data types from programming languages to overcome the constraints of standard Petri nets and allow the modelling of large-scale systems in a compact, parameterised and scalable way.

Our contributions

Multiscale attributes

We have identified the following attributes of multiscale biological systems:

  • repetition,
  • variation,
  • spatial organization,
  • hierarchical organization,
  • communication,
  • mobility,
  • replication,
  • deletion.

Modelling methodology

Our concrete contribution to the area is the development of a suitable methodology to underpin the process of engineering robust and useful models for complex biological systems which are characterized by one or several of these attributes.

Hierarchically Coloured Petri nets (HCPN)

We have developed a general approach for modelling and analyzing multiscale systems which combines the above two concepts, Hierarchically Coloured Petri nets (HCPN).

In this project we have explored the power of our approach for describing spatial multiscale problems in biological systems by complex and challenging case studies, which require computational experiments over very large underlying models.

Case studies

The case studies included:

latest update: December 07, 2011, at 10:30 AM