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

Li, Chen and Donizelli, Marco and Rodriguez, Nicolas and Dharuri, Harish and Endler, Lukas and Chelliah, Vijayalakshmi and Li, Lu and He, Enuo and Henry, Arnaud and Stefan, Melanie I. and Snoep, Jacky L. and Hucka, Michael and Le Novère, Nicolas and Laibe, Camille (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Systems Biology, 4 . Art. No. 92. ISSN 1752-0509. PMCID PMC2909940. https://resolver.caltech.edu/CaltechAUTHORS:20101025-144736877

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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/ 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/ under the GNU General Public License.


Item Type:Article
Related URLs:
URLURL TypeDescription
http://dx.doi.org/10.1186/1752-0509-4-92 DOIArticle
http://www.biomedcentral.com/1752-0509/4/1/92PublisherArticle
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2909940/PubMed CentralArticle
ORCID:
AuthorORCID
Hucka, Michael0000-0001-9105-5960
Le Novère, Nicolas0000-0002-6309-7327
Additional Information:© 2010 Li et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Received: 12 March 2010 Accepted: 29 June 2010. Published: 29 June 2010. BioModels Database is being developed by the Computational Systems Neurobiology group (EMBL-European Bioinformatics Institute, United-Kingdom). Collaborators include the SBML Team (California Institute of Technology, USA), the Database Of Quantitative Cellular Signalling (National Center for Biological Sciences, India), the Virtual Cell (University of Connecticut Health Center, USA), JWS Online (Stellenbosch University, ZA) and the CellML team (Auckland Bioengineering Institute, NZ). The development of BioModels Database is funded by the European Molecular Biology Laboratory (Computational Systems Neurobiology group), the Biotechnology and Biological Sciences Research Council (Computational Systems Neurobiology group, grant BB/F010516/1), the National Institute of General Medical Sciences (SBML Team and Computational Systems Neurobiology group, grant R01 GM070923). BioModels Database also benefited from funds of the DARPA (Herbert Sauro, Washington University, Seattle, USA). The authors would like to thank the members of the BioModels Database Scientific Advisory Board (SAB): Upinder Bhalla, MH, Pedro Mendes, Ion Moraru, Herbert Sauro and JLS. All the contributors of the models of the month: VC, Ranjita Dutta Roy, LE, EH, Noriko Hiroi, Nick Juty, Christian Knüpfer, NLN, LL, Michele Mattioni, Antonia Mayer, Anika Oellrich, Renaud Schiappa, MIS, Dominic P. Tolle and Judith Zaugg. The authors also thank Nick Juty, who read and corrected this manuscript thoroughly. The BioModels Database team would also like to express their gratitude to all the people who have given BioModels Database the opportunity to keep improving with their continuous support, including the contribution of models, software tools and constructive comments and criticisms. Authors' contributions: The work presented here was carried out by the authors in collaboration: CLi and MD, original developers of BioModels Database; LL and NR, converter and export developers; HD, LE, VC and EH, created, curated and annotated models; MIS, coordinator of the Model of the month; AH, developed the SBML to Bio- PAX converter; JLS, developed and maintained JWS Online; MH, provided coordination, SBML knowledge and grant support; NLN, curation, project instigation and coordination; CLaibe, feature development and current project coordinator. All authors have read and approved the final manuscript.
Funders:
Funding AgencyGrant Number
European Molecular Biology Laboratory (EMBL)UNSPECIFIED
Biotechnology and Biological Sciences Research Council (BBSRC)BB/F010516/1
NIHR01 GM070923
PubMed Central ID:PMC2909940
Record Number:CaltechAUTHORS:20101025-144736877
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20101025-144736877
Official Citation:Li et al., BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models BMC Systems Biology 2010, 4:92
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:20516
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:30 Nov 2010 22:57
Last Modified:09 Mar 2020 13:18

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