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Open Access Highly Accessed Database

BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models

Chen Li1, Marco Donizelli1, Nicolas Rodriguez1, Harish Dharuri2, Lukas Endler1, Vijayalakshmi Chelliah1, Lu Li1, Enuo He12, Arnaud Henry1, Melanie I Stefan1, Jacky L Snoep3, Michael Hucka2, Nicolas Le Novère1 and Camille Laibe1*

Author affiliations

1 European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK

2 Division of Engineering and Applied Science, California Institute of Technology, Pasadena, CA 91125, USA

3 Department of Biochemistry, Stellenbosch University, Private Bag X1, Matieland 7602, South Africa

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Citation and License

BMC Systems Biology 2010, 4:92  doi:10.1186/1752-0509-4-92

Published: 29 June 2010

Abstract

Background

Quantitative models of biochemical and cellular systems are used to answer a variety of questions in the biological sciences. The number of published quantitative models is growing steadily thanks to increasing interest in the use of models as well as the development of improved software systems and the availability of better, cheaper computer hardware. To maximise the benefits of this growing body of models, the field needs centralised model repositories that will encourage, facilitate and promote model dissemination and reuse. Ideally, the models stored in these repositories should be extensively tested and encoded in community-supported and standardised formats. In addition, the models and their components should be cross-referenced with other resources in order to allow their unambiguous identification.

Description

BioModels Database http://www.ebi.ac.uk/biomodels/ webcite is aimed at addressing exactly these needs. It is a freely-accessible online resource for storing, viewing, retrieving, and analysing published, peer-reviewed quantitative models of biochemical and cellular systems. The structure and behaviour of each simulation model distributed by BioModels Database are thoroughly checked; in addition, model elements are annotated with terms from controlled vocabularies as well as linked to relevant data resources. Models can be examined online or downloaded in various formats. Reaction network diagrams generated from the models are also available in several formats. BioModels Database also provides features such as online simulation and the extraction of components from large scale models into smaller submodels. Finally, the system provides a range of web services that external software systems can use to access up-to-date data from the database.

Conclusions

BioModels Database has become a recognised reference resource for systems biology. It is being used by the community in a variety of ways; for example, it is used to benchmark different simulation systems, and to study the clustering of models based upon their annotations. Model deposition to the database today is advised by several publishers of scientific journals. The models in BioModels Database are freely distributed and reusable; the underlying software infrastructure is also available from SourceForge https://sourceforge.net/projects/biomodels/ webcite under the GNU General Public License.