Annotation of SBML models through rule-based semantic integration
<p>Abstract</p> <p>Background</p> <p>The creation of accurate quantitative Systems Biology Markup Language (SBML) models is a time-intensive, manual process often complicated by the many data sources and formats required to annotate even a small and well-scoped model. I...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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BMC
2010-06-01
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| Series: | Journal of Biomedical Semantics |
| _version_ | 1811297011856572416 |
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| author | Lister Allyson L Lord Phillip Pocock Matthew Wipat Anil |
| author_facet | Lister Allyson L Lord Phillip Pocock Matthew Wipat Anil |
| author_sort | Lister Allyson L |
| collection | DOAJ |
| description | <p>Abstract</p> <p>Background</p> <p>The creation of accurate quantitative Systems Biology Markup Language (SBML) models is a time-intensive, manual process often complicated by the many data sources and formats required to annotate even a small and well-scoped model. Ideally, the retrieval and integration of biological knowledge for model annotation should be performed quickly, precisely, and with a minimum of manual effort.</p> <p>Results</p> <p>Here we present rule-based mediation, a method of semantic data integration applied to systems biology model annotation. The heterogeneous data sources are first syntactically converted into ontologies, which are then aligned to a small domain ontology by applying a rule base. We demonstrate proof-of-principle of this application of rule-based mediation using off-the-shelf semantic web technology through two use cases for SBML model annotation. Existing tools and technology provide a framework around which the system is built, reducing development time and increasing usability.</p> <p>Conclusions</p> <p>Integrating resources in this way accommodates multiple formats with different semantics, and provides richly-modelled biological knowledge suitable for annotation of SBML models. This initial work establishes the feasibility of rule-based mediation as part of an automated SBML model annotation system.</p> <p>Availability</p> <p>Detailed information on the project files as well as further information on and comparisons with similar projects is available from the project page at <url>http://cisban-silico.cs.ncl.ac.uk/RBM/</url>.</p> |
| first_indexed | 2024-04-13T05:57:55Z |
| format | Article |
| id | doaj.art-7f94badcce5a41da925d8cdcae66658b |
| institution | Directory Open Access Journal |
| issn | 2041-1480 |
| language | English |
| last_indexed | 2024-04-13T05:57:55Z |
| publishDate | 2010-06-01 |
| publisher | BMC |
| record_format | Article |
| series | Journal of Biomedical Semantics |
| spelling | doaj.art-7f94badcce5a41da925d8cdcae66658b2022-12-22T02:59:33ZengBMCJournal of Biomedical Semantics2041-14802010-06-011Suppl 1S310.1186/2041-1480-1-S1-S3Annotation of SBML models through rule-based semantic integrationLister Allyson LLord PhillipPocock MatthewWipat Anil<p>Abstract</p> <p>Background</p> <p>The creation of accurate quantitative Systems Biology Markup Language (SBML) models is a time-intensive, manual process often complicated by the many data sources and formats required to annotate even a small and well-scoped model. Ideally, the retrieval and integration of biological knowledge for model annotation should be performed quickly, precisely, and with a minimum of manual effort.</p> <p>Results</p> <p>Here we present rule-based mediation, a method of semantic data integration applied to systems biology model annotation. The heterogeneous data sources are first syntactically converted into ontologies, which are then aligned to a small domain ontology by applying a rule base. We demonstrate proof-of-principle of this application of rule-based mediation using off-the-shelf semantic web technology through two use cases for SBML model annotation. Existing tools and technology provide a framework around which the system is built, reducing development time and increasing usability.</p> <p>Conclusions</p> <p>Integrating resources in this way accommodates multiple formats with different semantics, and provides richly-modelled biological knowledge suitable for annotation of SBML models. This initial work establishes the feasibility of rule-based mediation as part of an automated SBML model annotation system.</p> <p>Availability</p> <p>Detailed information on the project files as well as further information on and comparisons with similar projects is available from the project page at <url>http://cisban-silico.cs.ncl.ac.uk/RBM/</url>.</p> |
| spellingShingle | Lister Allyson L Lord Phillip Pocock Matthew Wipat Anil Annotation of SBML models through rule-based semantic integration Journal of Biomedical Semantics |
| title | Annotation of SBML models through rule-based semantic integration |
| title_full | Annotation of SBML models through rule-based semantic integration |
| title_fullStr | Annotation of SBML models through rule-based semantic integration |
| title_full_unstemmed | Annotation of SBML models through rule-based semantic integration |
| title_short | Annotation of SBML models through rule-based semantic integration |
| title_sort | annotation of sbml models through rule based semantic integration |
| work_keys_str_mv | AT listerallysonl annotationofsbmlmodelsthroughrulebasedsemanticintegration AT lordphillip annotationofsbmlmodelsthroughrulebasedsemanticintegration AT pocockmatthew annotationofsbmlmodelsthroughrulebasedsemanticintegration AT wipatanil annotationofsbmlmodelsthroughrulebasedsemanticintegration |