Systems biology is an approach by which biological questions are addressed through integrating data collection activities with computational/mathematical modelling activities to produce a better understanding of biological systems (or sub-systems).
Methods for integrating data into models can be varied and multiple to suit the system under investigation but may include a combination of mathematical, statistical and computational modelling, visualisation tools and network inference. The model should capture complex biological behaviour by integrating the necessary components and interactions to produce a framework that models the biological system and from which useful predictions about that system can be made and tested. Data-testing and model development should proceed iteratively, to improve the knowledge of the system.
A systems biology project may be performed at a number of biological scales, or may integrate across scales (e.g. within cells, between cells, between tissues, between individuals, between species) depending on the biological question to be answered. Systems approaches are most relevant when there is a clear biological endpoint.
Diagram showing the interaction and contrast between a traditional approach (blue) and a systems biology approach (pink) - click for enlarged version.
We support world class research and training in systems biology through a range of mechanisms and facilitate international partnerships for the benefit of UK science in this area. We are a partner in the European Research Area Network ERASysBio, a transnational initiative to support the convergence of life sciences with information technology and systems science.
Through Exploiting Systems Biology LINK we have funded a project studying the regulatory network controlling tomato ripening. It is being carried out jointly with the Royal Holloway, University of London and Syngenta at the BBSRC/EPSRC Centre for Systems Biology at the University of Nottingham.
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