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Annotation of SBML Models Through Rule-Based Semantic Integration Nature Precedings
Allyson L. Lister; Phillip Lord; Matthew Pocock; Anil Wipat.
*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...
Tipo: Manuscript Palavras-chave: Bioinformatics; Data Standards.
Ano: 2009 URL: http://precedings.nature.com/documents/3286/version/1
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