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. 2010 Jun 29;4:92.
doi: 10.1186/1752-0509-4-92.

BioModels Database: An Enhanced, Curated and Annotated Resource for Published Quantitative Kinetic Models

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Free PMC article

BioModels Database: An Enhanced, Curated and Annotated Resource for Published Quantitative Kinetic Models

Chen Li et al. BMC Syst Biol. .
Free PMC article

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.

Figures

Figure 1
Figure 1
Database structure. Shown here is a schematic of the relational database structure used by BioModels Database. It depicts the different database tables and their relationships. The three main steps of the pipeline (curation, annotation and publication) are organized by the three main tables, cura, anno and publ, respectively. The two branches can be distinguished by the fact that the tables related to the non-curated branch are prefixed with uncura.
Figure 2
Figure 2
BioModels Database pipeline. The BioModels Database pipeline encompasses all the steps undergone by each model, from its submission to its publication. This figure illustrates the sequence of steps. It encompasses both public branches of the database (curated and non-curated) as well as the possibility of curating and annotating models already published in the non-curated branch.
Figure 3
Figure 3
Models tree based on Gene Ontology. BioModels Database provides users with three primary facilities for finding and discovering models: the system's search interface, the browsable list of all models, and an alternative list based on Gene Ontology (GO) terms. A screen image of the last alternative is shown here. The GO-based view is derived from the annotations of models in the database; the annotations of all models are collected and used to generate a pruned GO tree, and this tree can be browsed in order to find models annotated with a specific GO term.
Figure 4
Figure 4
Thematic content of models. Categorisation of models in BioModels Database using the Gene Ontology (GO) terms present in each model's annotations. This chart was generated by enumerating models in the database whose annotations refer to children of the GO terms listed here, after first removing certain GO terms (translation, GO:0006350; transcription, GO:0006412; and cellular metabolic process, GO:0044237) that appear across different categories, and hence would have biased the analysis.
Figure 5
Figure 5
Search engine. The BioModels Database search engine processes three different types of data in order to provide an accurate result. First, it searches the annotations (by querying the internal database), then the models (using Lucene), and finally, data linked from external resources. Searching for the last is accomplished via direct connection to remote databases and by using remote web services. Ultimately, all the results are collected, processed to remove duplicates, then classified based on which branch the models come from, ordered, and finally, returned to the user.
Figure 6
Figure 6
Taxonomic search. When a user's search is based on a taxonomic term, the BioModels Database search algorithm considers the entire taxonomic hierarchy. For example, searching for the term "mammalia" will catch not only models annotated with the term Mammalia, but also models annotated with terms related to it, such as Metazoa, Homo sapiens or Rattus norvegicus (represented in red in this figure).
Figure 7
Figure 7
View of a model page. This screen image shows the interface of BioModels Database as it displays the model Kholodenko1999 EGFRsignaling (BIOMD0000000048). As illustrated here, the display of a model in the system is divided into several areas. The areas have been highlighted and numbered here for discussion purposes. The first area, across the top, contains general links for accessing the various features of BioModels Database. The second allows the user to perform actions specific to the model currently displayed (for example, to download the model in various formats or simulate it online). The third area contains all the different views of the model in separate tabbed window panes; each tabbed area is dedicated to a given aspect of the model (e.g., overview, mathematics, model entities, parameters, curation information, etc.). The fourth area is used to display content specific to the currently selected view of the model.
Figure 8
Figure 8
Growth of BioModels Database. Graph depicting the number of models (green) and the number of reactions (yellow) stored in BioModels Database at each release of the database made so far. The number of reactions includes SBML "rate rules", since some models only use rate rules. The graph illustrates that not only has the number of models increased approximately ten-fold since 2005, but the average complexity of those models has nearly tripled in the same period.

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