BioModels Edit

Citations: 686

z-index: 52.77

Basic information
Short name BioModels
Full name BioModels Database
Description A repository of peer-reviewed, published, computational models. BioModels hosts a vast selection of existing literature-based physiologically and pharmaceutically relevant mechanistic models in standard formats.
URL http://www.ebi.ac.uk/biomodels/
Year founded 2005
Last update & version 2019-4-8 release 31
Availability Free to all users
Contact information
University/Institution hosted European Bioinformatics Institute
Address European Bioinformatics Institute EMBL, Wellcome-Trust Genome Campus, Hinxton, CB10 1SD, UK.
City
Province/State
Country/Region United Kingdom
Contact name (PI/Team) BioModels.net Team
Contact email (PI/Helpdesk) biomodels-cura@ebi.ac.uk
Data information
Data object
Data type
Database category
Major organism
Keyword
Publications
  • BioModels: expanding horizons to include more modelling approaches and formats. [PMID: 29106614]
    Glont M, Nguyen TVN, Graesslin M, Hälke R, Ali R, Schramm J, Wimalaratne SM, Kothamachu VB, Rodriguez N, Swat MJ, Eils J, Eils R, Laibe C, Malik-Sheriff RS, Chelliah V, Le Novère N, Hermjakob H.

    BioModels serves as a central repository of mathematical models representing biological processes. It offers a platform to make mathematical models easily shareable across the systems modelling community, thereby supporting model reuse. To facilitate hosting a broader range of model formats derived from diverse modelling approaches and tools, a new infrastructure for BioModels has been developed that is available at http://www.ebi.ac.uk/biomodels. This new system allows submitting and sharing of a wide range of models with improved support for formats other than SBML. It also offers a version-control backed environment in which authors and curators can work collaboratively to curate models. This article summarises the features available in the current system and discusses the potential benefit they offer to the users over the previous system. In summary, the new portal broadens the scope of models accepted in BioModels and supports collaborative model curation which is crucial for model reproducibility and sharing.

    Nucleic Acids Res 2018:46(D1)

    2 Citations (from Europe PMC, 2019-04-15)

  • BioModels: ten-year anniversary. [PMID: 25414348]
    Vijayalakshmi Chelliah, Nick Juty, Ishan Ajmera, Raza Ali, Marine Dumousseau, Mihai Glont, Michael Hucka, Gaël Jalowicki, Sarah Keating, Vincent Knight-Schrijver, Audald Lloret-Villas, Kedar Nath Natarajan, Jean-Baptiste Pettit, Nicolas Rodriguez, Michael Schubert, Sarala M Wimalaratne, Yangyang Zhao, Henning Hermjakob, Nicolas Le Novère, Camille Laibe

    BioModels (http://www.ebi.ac.uk/biomodels/) is a repository of mathematical models of biological processes. A large set of models is curated to verify both correspondence to the biological process that the model seeks to represent, and reproducibility of the simulation results as described in the corresponding peer-reviewed publication. Many models submitted to the database are annotated, cross-referencing its components to external resources such as database records, and terms from controlled vocabularies and ontologies. BioModels comprises two main branches: one is composed of models derived from literature, while the second is generated through automated processes. BioModels currently hosts over 1200 models derived directly from the literature, as well as in excess of 140,000 models automatically generated from pathway resources. This represents an approximate 60-fold growth for literature-based model numbers alone, since BioModels' first release a decade ago. This article describes updates to the resource over this period, which include changes to the user interface, the annotation profiles of models in the curation pipeline, major infrastructure changes, ability to perform online simulations and the availability of model content in Linked Data form. We also outline planned improvements to cope with a diverse array of new challenges.

    Nucleic Acids Res 2015:43(Database issue)

    102 Citations (from Europe PMC, 2019-04-13)

  • BioModels Database: a repository of mathematical models of biological processes. [PMID: 23715986]
    Chelliah V, Laibe C, Le Novère N.

    BioModels Database is a public online resource that allows storing and sharing of published, peer-reviewed quantitative, dynamic models of biological processes. The model components and behaviour are thoroughly checked to correspond the original publication and manually curated to ensure reliability. Furthermore, the model elements are annotated with terms from controlled vocabularies as well as linked to relevant external data resources. This greatly helps in model interpretation and reuse. Models are stored in SBML format, accepted in SBML and CellML formats, and are available for download in various other common formats such as BioPAX, Octave, SciLab, VCML, XPP and PDF, in addition to SBML. The reaction network diagram of the models is also available in several formats. BioModels Database features a search engine, which provides simple and more advanced searches. Features such as online simulation and creation of smaller models (submodels) from the selected model elements of a larger one are provided. BioModels Database can be accessed both via a web interface and programmatically via web services. New models are available in BioModels Database at regular releases, about every 4 months.

    Methods Mol Biol 2013:1021()

    33 Citations (from Europe PMC, 2019-04-15)

  • Path2Models: large-scale generation of computational models from biochemical pathway maps. [PMID: 24180668]
    Büchel F, Rodriguez N, Swainston N, Wrzodek C, Wrzodek C, Czauderna T, Keller R, Mittag F, Schubert M, Glont M, Golebiewski M, van Iersel M, Keating S, Rall M, Wybrow M, Hermjakob H, Hucka M, Kell DB, Müller W, Mendes P, Zell A, Chaouiya C, Saez-Rodriguez J, Schreiber F, Laibe C, Dräger A, Le Novère N.

    Systems biology projects and omics technologies have led to a growing number of biochemical pathway models and reconstructions. However, the majority of these models are still created de novo, based on literature mining and the manual processing of pathway data.To increase the efficiency of model creation, the Path2Models project has automatically generated mathematical models from pathway representations using a suite of freely available software. Data sources include KEGG, BioCarta, MetaCyc and SABIO-RK. Depending on the source data, three types of models are provided: kinetic, logical and constraint-based. Models from over 2 600 organisms are encoded consistently in SBML, and are made freely available through BioModels Database at http://www.ebi.ac.uk/biomodels-main/path2models. Each model contains the list of participants, their interactions, the relevant mathematical constructs, and initial parameter values. Most models are also available as easy-to-understand graphical SBGN maps.To date, the project has resulted in more than 140 000 freely available models. Such a resource can tremendously accelerate the development of mathematical models by providing initial starting models for simulation and analysis, which can be subsequently curated and further parameterized.

    BMC Syst Biol 2013:7()

    54 Citations (from Europe PMC, 2019-04-15)

  • BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. [PMID: 20587024]
    Chen Li, Marco Donizelli, Nicolas Rodriguez, Harish Dharuri, Lukas Endler, Vijayalakshmi Chelliah, Lu Li, Enuo He, Arnaud Henry, Melanie I Stefan, Jacky L Snoep, Michael Hucka, Nicolas Le Novère, Camille Laibe,

    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.

    BMC Syst Biol 2010:4()

    212 Citations (from Europe PMC, 2019-04-13)

  • BioModels Database: a free, centralized database of curated, published, quantitative kinetic models of biochemical and cellular systems. [PMID: 16381960]
    Nicolas Le Novère, Benjamin Bornstein, Alexander Broicher, Mélanie Courtot, Marco Donizelli, Harish Dharuri, Lu Li, Herbert Sauro, Maria Schilstra, Bruce Shapiro, Jacky L Snoep, Michael Hucka

    BioModels Database (http://www.ebi.ac.uk/biomodels/), part of the international initiative BioModels.net, provides access to published, peer-reviewed, quantitative models of biochemical and cellular systems. Each model is carefully curated to verify that it corresponds to the reference publication and gives the proper numerical results. Curators also annotate the components of the models with terms from controlled vocabularies and links to other relevant data resources. This allows the users to search accurately for the models they need. The models can currently be retrieved in the SBML format, and import/export facilities are being developed to extend the spectrum of formats supported by the resource.

    Nucleic Acids Res 2006:34(Database issue)

    283 Citations (from Europe PMC, 2019-04-13)

Rank

  • Ranking in all databases: No. 139
  • Ranking in category/categories:
    • Gene genome and annotation: No. 62
    • Pathway: No. 10
    • Standard ontology and nomenclature: No. 12
The box plots depict Z-index distribution for all databases in Database Commons and for specific database category/categories. The red line indicates log2(Z-index) of BioModels.

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Record metadata

  • Created on: 2018-01-28
    • ***ina@***c.cn [2019-04-15]
    • ***ina@***c.cn [2019-04-15]
    • ***ina@***c.cn [2019-04-15]
    • ***ina@***c.cn [2019-04-15]
    • ***imabatool@***u.edu.pk [2018-09-04]
    • ***ngyang17m@***c.cn [2018-02-22]
    • ***130785@***m [2018-01-27]

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