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...
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doaj-7f94badcce5a41da925d8cdcae66658b2020-11-25T01:36:56ZengBMCJournal 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> |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Lister Allyson L Lord Phillip Pocock Matthew Wipat Anil |
spellingShingle |
Lister Allyson L Lord Phillip Pocock Matthew Wipat Anil Annotation of SBML models through rule-based semantic integration Journal of Biomedical Semantics |
author_facet |
Lister Allyson L Lord Phillip Pocock Matthew Wipat Anil |
author_sort |
Lister Allyson L |
title |
Annotation of SBML models through rule-based semantic integration |
title_short |
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_sort |
annotation of sbml models through rule-based semantic integration |
publisher |
BMC |
series |
Journal of Biomedical Semantics |
issn |
2041-1480 |
publishDate |
2010-06-01 |
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> |
work_keys_str_mv |
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