Email updates

Keep up to date with the latest news and content from Journal of Biomedical Semantics and BioMed Central.

This article is part of the supplement: Proceedings of the Bio-Ontologies Special Interest Group Meeting 2010

Open Access Proceedings

HyQue: evaluating hypotheses using Semantic Web technologies

Alison Callahan1, Michel Dumontier1* and Nigam H Shah2

Author Affiliations

1 Department of Biology, Carleton University, Ottawa, Ontario, Canada

2 Stanford Center for Biomedical Informatics Research, Stanford University, Stanford California, USA

For all author emails, please log on.

Journal of Biomedical Semantics 2011, 2(Suppl 2):S3  doi:10.1186/2041-1480-2-S2-S3

Published: 17 May 2011

Abstract

Background

Key to the success of e-Science is the ability to computationally evaluate expert-composed hypotheses for validity against experimental data. Researchers face the challenge of collecting, evaluating and integrating large amounts of diverse information to compose and evaluate a hypothesis. Confronted with rapidly accumulating data, researchers currently do not have the software tools to undertake the required information integration tasks.

Results

We present HyQue, a Semantic Web tool for querying scientific knowledge bases with the purpose of evaluating user submitted hypotheses. HyQue features a knowledge model to accommodate diverse hypotheses structured as events and represented using Semantic Web languages (RDF/OWL). Hypothesis validity is evaluated against experimental and literature-sourced evidence through a combination of SPARQL queries and evaluation rules. Inference over OWL ontologies (for type specifications, subclass assertions and parthood relations) and retrieval of facts stored as Bio2RDF linked data provide support for a given hypothesis. We evaluate hypotheses of varying levels of detail about the genetic network controlling galactose metabolism in Saccharomyces cerevisiae to demonstrate the feasibility of deploying such semantic computing tools over a growing body of structured knowledge in Bio2RDF.

Conclusions

HyQue is a query-based hypothesis evaluation system that can currently evaluate hypotheses about the galactose metabolism in S. cerevisiae. Hypotheses as well as the supporting or refuting data are represented in RDF and directly linked to one another allowing scientists to browse from data to hypothesis and vice versa. HyQue hypotheses and data are available at http://semanticscience.org/projects/hyque webcite.