Abstract
BackgroundBioModels Database is a reference repository of mathematical models used in biology. Models are stored as SBML files on a file system and metadata is provided in a relational database. Models can be retrieved through a web interface and programmatically via web services. In addition to those more traditional ways to access information, Linked Data using Semantic Web technologies (such as the Resource Description Framework, RDF), is becoming an increasingly popular means to describe and expose biological relevant data.ResultsWe present the BioModels Linked Dataset, which exposes the models’ content as a dereferencable interlinked dataset. BioModels Linked Dataset makes use of the wealth of annotations available within a large number of manually curated models to link and integrate data and models from other resources.ConclusionsThe BioModels Linked Dataset provides users with a dataset interoperable with other semantic web resources. It supports powerful search queries, some of which were not previously available to users and allow integration of data from multiple resources. This provides a distributed platform to find similar models for comparison, processing and enrichment.
Highlights
BioModels Database is a reference repository of mathematical models used in biology
This paper describes the BioModels Linked Dataset using BioModels Database release 27, from Apr 2014
The Systems Biology Markup Language (SBML) and Resource Description Framework (RDF) files for this release can be downloaded from: ftp://ftp.ebi.ac.uk/pub/databases/biomodels/releases/201404-11/. This includes all models published in the literature, together with the SBML RDF schema and a dataset description which contains metadata about the dataset
Summary
BioModels Database is a reference repository of mathematical models used in biology. Models are stored as SBML files on a file system and metadata is provided in a relational database. Models can be retrieved through a web interface and programmatically via web services In addition to those more traditional ways to access information, Linked Data using Semantic Web technologies (such as the Resource Description Framework, RDF), is becoming an increasingly popular means to describe and expose biological relevant data. BioModels Database [1] was developed to support the storage, search and retrieval of these models It provides around 1200 models published in the scientific literature (a large portion of which are manually curated) and over 142,000 models automatically generated from pathway resources [2] such as from KEGG [3], BioCarta [4], MetaCyc [5] SABIO-RK [6] and PID [7]. The relationship between each annotated model component and the accompanying cross-reference
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