Annotation of SBML Models Through Rule-Based Semantic Integration
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- Centre for Integrated Systems Biology of Ageing and Nutrition (CISBAN), Newcastle University
- Newcastle University
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- Document Type:
- Manuscript
- Date:
- Received 26 May 2009 13:27 UTC; Posted 29 May 2009
- Subjects:
- Bioinformatics
- Abstract:
Motivation: 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. Here, we present a method using off-the-shelf semantic web technology which enables this process: the heterogeneous data sources are first syntactically converted into ontologies; these are then aligned to a small domain ontology by applying a rule base. Integrating resources in this way can accommodate multiple formats with different semantics; it provides richly modelled biological knowledge suitable for annotation of SBML models.
Results: We demonstrate proof-of-principle for this rule-based mediation with two use cases for SBML model annotation. This was implemented with existing tools, decreasing development time and increasing reusability. This initial work establishes the feasibility of this approach as part of an automated SBML model annotation system.
Availability: Detailed information including download and mapping of the ontologies as well as integration results is available from http://www.cisban.ac.uk/RBM
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- This document is licensed to the public under the Creative Commons Attribution 3.0 License
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Lister, Allyson, Lord, Phillip, Pocock, Matthew , and Wipat, Anil. Annotation of SBML Models Through Rule-Based Semantic Integration. Available from Nature Precedings <http://hdl.handle.net/10101/npre.2009.3286.1> (2009)
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Allyson LIster on 21 August 2009 09:43 UTC
This document was accepted and presented at the Bio-Ontologies SIG for ISMB 2009, in Stockholm (http://www.bio-ontologies.org.uk/). It was also published in the proceedings (http://www.bio-ontologies.org.uk/download/Bio-Ontologies2009.pdf). It is presented here as a permanent link to this article, on its own.