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Due to the complexity of biological systems, interpretation of data obtained by a single experimental approach can often be interpreted only if viewed from a broader context, taking into account the information obtained by many diverse techniques. The vast amount of interpreted experimental data that is now available via the internet opens the possibility of collecting the relevant pieces of information that will enable scientists to form hypotheses based on the integration of this diverse information. However, the sheer volume of data that is available makes it very difficult to select the information necessary to make a coherent model of the biological system under study. We are developing an integrated semantic methodology to address this challenge, with the current emphasis of supporting bioinformatics applications in glycomics. Our ontology-driven methodology starts with the development of a domain ontology (or interrelated domain ontologies) and associated models for supporting trust and provenance, and leads to semantic search, browsing, and integration, further aiding in analysis of experimental data and heterogeneous documents.


Presented at the W3C Workshop on Semantic Web for Life Sciences, Cambridge, MA, October 27-28, 2004.

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W3C Presentation.pdf (1041 kB)