Computational Systems Biology

Computational biology images.

As more is discovered about the structure, organisation and behaviour of cells, tissues, organisms and communities of biological systems the need to understand how all of these systems and phenomena work and interact in a holistic fashion becomes more urgent.

The promise of being able to use the power of computers and of recent computational and mathematical modelling techniques to understand and predict important aspects of the behaviour of biological systems is an exciting and vitally important opportunity for medicine and biology.

The Computational Biology Group at Sheffield is at the forefront of this endeavour and is working extremely closely with experimental biologists and clinicians in building realistic and useful models of biological phenomena from the molecular level, to the cellular, tissue, organismal and social levels.

There are two basic approaches to the problem of modelling:

  • The traditional technique is ‘top-down’ modelling. This works well for very large ‘statistically significant’ numbers of entities – whether cells or proteins. These can be modelled using classical mathematical techniques such as differential equations.
  • ‘Bottom-up’ modelling works well with small numbers of entities, as each entity is represented by a software agent. The interaction of software agents in a computer should mimic real life interactions, allowing the software model to predict the behaviour of a similar biological system.

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