BioModels Database: a Unified resource for Systems Biology models

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Even the simplest living organisms perform a huge number of different processes, which are interconnected in complex ways to ensure that the organism responds appropriately to its environment. One of the ways of ensuring that we really understand how these processes fit together is to build quantitative models of them, that can be simulated using computer. If a computer simulation behaves differently than the real organism, we know that we've neglected an important component of the system. Quantitative models can also reveal previously unappreciated properties of complex systems, for instance paving the way toward new drug treatments. This approach, known as 'Computational Systems Biology', is becoming increasingly popular now that scientists are accumulating detailed parts lists for many organisms, thanks to the 'omics' efforts to comprehensively document the components of living entities. BioModels Database provides access to quantitative models of biochemical and cell biological systems that have been published in the scientific literature, and verified to be accurate. Some of these models are very simple, containing just a few processes or reactions; others contain hundreds. The models are checked to verify that they behave as described in the reference publication. Human curators annotate and cross link components of the models to other relevant data resources. This allows users to identify precisely the components of models, and helps them to retrieve appropriate models, which they can then visualise and simulate using appropriate software. For instance, in order to develop a quantitative model of cell tumorigenesis, one may choose a suitable model of cell-cycle, and attempt to merge it with models of relevant cell signalling pathways such as the MAP kinase cascade. Only a database of trusted, peer-reviewed, annotated models will provide the adequate choice of 'building bricks'. Users can search models on many different criteria, visualise and and download them in various standard formats for further use. Over the last two years, BioModels Database has undergone an exponential growth. It is now the reference data resource for quantitative models. Deposition of models upon publication is advised by several scientific journals, and the atabase has been voted most used data resource in Systems Biology by an independent community survey. Developed as a proof of concept, BioModels Database has demonstrated its relevance and needs to evolve in a more mature resource in order to best serve the need of a growing UK Systems Biology community.