I can’t resist posting a short announcement about two papers I’m an author on which have been accepted to this year’s Bio-Ontologies SIG at ISMB. 🙂 I’ll post more about both papers during or just before the SIG, which is on Sunday, June 28, 2009. However, here’s a taster of both.
I am first author on one of the papers, which covers the current state of work on my PhD: “Annotation of SBML Models Through Rule-Based Semantic Integration”, by Allyson L. Lister, Phillip Lord, Matthew Pocock, and Anil Wipat. Here’s the 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.
And to whet the appetite a little further, here’s an overview diagram from the paper describing the overall flow through the data integration process:
The second paper discusses the Ontology for Biomedical Investigations (OBI) (OWL file, website): “Modeling biomedical experimental processes with OBI”, by the OBI Consortium (of which I am a part). You can read the full paper, and here is the abstract:
Motivation: Experimental metadata are stored in many different formats and styles, creating challenges in comparison, reproduction and analysis. These difficulties impose severe limitations on the usability of such metadata in a wider context. The Ontology for Biomedical Investigations (OBI), developed as part of a global, cross-community effort, provides an approach to represent biological and clinical investigations in an explicit and integrative framework which facilitates computational processing and semantic web compatibility. Here we detail two real-world applications of OBI and show how OBI satisfies such use cases.