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BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models
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...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2010
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2909940/ https://www.ncbi.nlm.nih.gov/pubmed/20587024 http://dx.doi.org/10.1186/1752-0509-4-92 |
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author | Li, Chen Donizelli, Marco Rodriguez, Nicolas Dharuri, Harish Endler, Lukas Chelliah, Vijayalakshmi Li, Lu He, Enuo Henry, Arnaud Stefan, Melanie I Snoep, Jacky L Hucka, Michael Le Novère, Nicolas Laibe, Camille |
author_facet | Li, Chen Donizelli, Marco Rodriguez, Nicolas Dharuri, Harish Endler, Lukas Chelliah, Vijayalakshmi Li, Lu He, Enuo Henry, Arnaud Stefan, Melanie I Snoep, Jacky L Hucka, Michael Le Novère, Nicolas Laibe, Camille |
author_sort | Li, Chen |
collection | PubMed |
description | 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. |
format | Text |
id | pubmed-2909940 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-29099402010-07-27 BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models Li, Chen Donizelli, Marco Rodriguez, Nicolas Dharuri, Harish Endler, Lukas Chelliah, Vijayalakshmi Li, Lu He, Enuo Henry, Arnaud Stefan, Melanie I Snoep, Jacky L Hucka, Michael Le Novère, Nicolas Laibe, Camille BMC Syst Biol Database 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. BioMed Central 2010-06-29 /pmc/articles/PMC2909940/ /pubmed/20587024 http://dx.doi.org/10.1186/1752-0509-4-92 Text en Copyright ©2010 Li et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 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. |
spellingShingle | Database Li, Chen Donizelli, Marco Rodriguez, Nicolas Dharuri, Harish Endler, Lukas Chelliah, Vijayalakshmi Li, Lu He, Enuo Henry, Arnaud Stefan, Melanie I Snoep, Jacky L Hucka, Michael Le Novère, Nicolas Laibe, Camille BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models |
title | BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models |
title_full | BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models |
title_fullStr | BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models |
title_full_unstemmed | BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models |
title_short | BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models |
title_sort | biomodels database: an enhanced, curated and annotated resource for published quantitative kinetic models |
topic | Database |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2909940/ https://www.ncbi.nlm.nih.gov/pubmed/20587024 http://dx.doi.org/10.1186/1752-0509-4-92 |
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