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OREMPdb: a semantic dictionary of computational pathway models.

Umeton R, Nicosia G, Dewey CF - BMC Bioinformatics (2012)

Bottom Line: OREMP has been applied to the curated branch of BioModels (2011/04/15 release) which overall contains 326 models, 9244 reactions, and 5636 species.OREMPdb is the semantic dictionary created as a result, which is made of 7360 species-sets.For each one of these sets, OREMPdb links the original pathway and the link to the original paper where this information first appeared.

View Article: PubMed Central - HTML - PubMed

Affiliation: Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA.

ABSTRACT

Background: The information coming from biomedical ontologies and computational pathway models is expanding continuously: research communities keep this process up and their advances are generally shared by means of dedicated resources published on the web. In fact, such models are shared to provide the characterization of molecular processes, while biomedical ontologies detail a semantic context to the majority of those pathways. Recent advances in both fields pave the way for a scalable information integration based on aggregate knowledge repositories, but the lack of overall standard formats impedes this progress. Indeed, having different objectives and different abstraction levels, most of these resources "speak" different languages. Semantic web technologies are here explored as a means to address some of these problems.

Methods: Employing an extensible collection of interpreters, we developed OREMP (Ontology Reasoning Engine for Molecular Pathways), a system that abstracts the information from different resources and combines them together into a coherent ontology. Continuing this effort we present OREMPdb; once different pathways are fed into OREMP, species are linked to the external ontologies referred and to reactions in which they participate. Exploiting these links, the system builds species-sets, which encapsulate species that operate together. Composing all of the reactions together, the system computes all of the reaction paths from-and-to all of the species-sets.

Results: OREMP has been applied to the curated branch of BioModels (2011/04/15 release) which overall contains 326 models, 9244 reactions, and 5636 species. OREMPdb is the semantic dictionary created as a result, which is made of 7360 species-sets. For each one of these sets, OREMPdb links the original pathway and the link to the original paper where this information first appeared.

Show MeSH
OREMP system architecture. System architecture: its components are integrated to work together preserving a flexible and easily extensible architecture. Each module has different versions used on the basis of job in progress (e.g., to parse an SBML Level 2 Version 1 file, it will be dynamically chosen the SBML 1 parser).
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Figure 2: OREMP system architecture. System architecture: its components are integrated to work together preserving a flexible and easily extensible architecture. Each module has different versions used on the basis of job in progress (e.g., to parse an SBML Level 2 Version 1 file, it will be dynamically chosen the SBML 1 parser).

Mentions: Biological processes can be effectively modeled by systems of ordinary differential equations (ODE). The equations themselves, along with their rate constants and initial conditions, need to be supplied to the ODE solver in a machine-readable format. A very popular standard format for describing the information content of models is the Systems Biology Markup Language (SBML) [14]. The SBML standard provides definitions for all model components that result in XML trees, that are machine-readable descriptions. Additionally, RDF parts inside SBML descriptions (e.g., annotations) can be expressed in XML and stored in XML repositories. A computational pathway models, or simply model, is a set of biochemical species whose evolution in time is determined by the reactions they participate in. These reactions, as well as the species, are specified in the SBML file. Reactions employ MathML [18] sections to specify how species concentration changes over time. Several ontologies [1] have recently been proposed to link species named in individual models to specific biological entities appearing in established curated biological information sources (e.g., GO, UniProt, ChEBI, and KEGG). A bio-ontology is an ontology where it is formally detailed how some life-science elements relate to each others. In order to step beyond simple syntactical translation, and exploit ontologies properly, we designed a system that merges the information from molecular pathways and curated biological ontologies into extended ontologies using a specific meta-format. The system is composed of the interchangeable and extensible components depicted in Figure 2; effectively, the information (e.g., species, reactions and references to ontologies) coming from heterogeneous resources is abstracted into an internal meta-format through these modular computational steps:


OREMPdb: a semantic dictionary of computational pathway models.

Umeton R, Nicosia G, Dewey CF - BMC Bioinformatics (2012)

OREMP system architecture. System architecture: its components are integrated to work together preserving a flexible and easily extensible architecture. Each module has different versions used on the basis of job in progress (e.g., to parse an SBML Level 2 Version 1 file, it will be dynamically chosen the SBML 1 parser).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3303718&req=5

Figure 2: OREMP system architecture. System architecture: its components are integrated to work together preserving a flexible and easily extensible architecture. Each module has different versions used on the basis of job in progress (e.g., to parse an SBML Level 2 Version 1 file, it will be dynamically chosen the SBML 1 parser).
Mentions: Biological processes can be effectively modeled by systems of ordinary differential equations (ODE). The equations themselves, along with their rate constants and initial conditions, need to be supplied to the ODE solver in a machine-readable format. A very popular standard format for describing the information content of models is the Systems Biology Markup Language (SBML) [14]. The SBML standard provides definitions for all model components that result in XML trees, that are machine-readable descriptions. Additionally, RDF parts inside SBML descriptions (e.g., annotations) can be expressed in XML and stored in XML repositories. A computational pathway models, or simply model, is a set of biochemical species whose evolution in time is determined by the reactions they participate in. These reactions, as well as the species, are specified in the SBML file. Reactions employ MathML [18] sections to specify how species concentration changes over time. Several ontologies [1] have recently been proposed to link species named in individual models to specific biological entities appearing in established curated biological information sources (e.g., GO, UniProt, ChEBI, and KEGG). A bio-ontology is an ontology where it is formally detailed how some life-science elements relate to each others. In order to step beyond simple syntactical translation, and exploit ontologies properly, we designed a system that merges the information from molecular pathways and curated biological ontologies into extended ontologies using a specific meta-format. The system is composed of the interchangeable and extensible components depicted in Figure 2; effectively, the information (e.g., species, reactions and references to ontologies) coming from heterogeneous resources is abstracted into an internal meta-format through these modular computational steps:

Bottom Line: OREMP has been applied to the curated branch of BioModels (2011/04/15 release) which overall contains 326 models, 9244 reactions, and 5636 species.OREMPdb is the semantic dictionary created as a result, which is made of 7360 species-sets.For each one of these sets, OREMPdb links the original pathway and the link to the original paper where this information first appeared.

View Article: PubMed Central - HTML - PubMed

Affiliation: Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA.

ABSTRACT

Background: The information coming from biomedical ontologies and computational pathway models is expanding continuously: research communities keep this process up and their advances are generally shared by means of dedicated resources published on the web. In fact, such models are shared to provide the characterization of molecular processes, while biomedical ontologies detail a semantic context to the majority of those pathways. Recent advances in both fields pave the way for a scalable information integration based on aggregate knowledge repositories, but the lack of overall standard formats impedes this progress. Indeed, having different objectives and different abstraction levels, most of these resources "speak" different languages. Semantic web technologies are here explored as a means to address some of these problems.

Methods: Employing an extensible collection of interpreters, we developed OREMP (Ontology Reasoning Engine for Molecular Pathways), a system that abstracts the information from different resources and combines them together into a coherent ontology. Continuing this effort we present OREMPdb; once different pathways are fed into OREMP, species are linked to the external ontologies referred and to reactions in which they participate. Exploiting these links, the system builds species-sets, which encapsulate species that operate together. Composing all of the reactions together, the system computes all of the reaction paths from-and-to all of the species-sets.

Results: OREMP has been applied to the curated branch of BioModels (2011/04/15 release) which overall contains 326 models, 9244 reactions, and 5636 species. OREMPdb is the semantic dictionary created as a result, which is made of 7360 species-sets. For each one of these sets, OREMPdb links the original pathway and the link to the original paper where this information first appeared.

Show MeSH