Charla: Using Data and Services in a Semantic Web Framework for Biochemical Knowledge Discovery

Michel Dumontier, Associate Professor of Bioinformatics at Carleton University
2 Diciembre, 2011 - 14:30
Auditorio DCC




Modern drug discovery requires access to machine-understandable data that can be searched, retrieved, and subsequently analyzed using a wide array of analytical software and services. In this presentation, I will demonstrate the prediction of chemical toxicity by reasoning over a set of chemical semantic web services  that i) retrieve data from Bio2RDF, the largest linked open data project for the life sciences, ii) compute chemical attributes using the open source Chemical Development Kit (CDK), and iii) ultimately make predictions using formalized (machine understandable) decision trees. I will show how one can make use of the SADI-enabled SHARE client to automatically identify and invoke the necessary chemical semantic web services by reasoning about formalized service inputs and outputs described using basic types and relations from OWL the Semanticscience Integrated Ontology (SIO) and descriptors from the Chemical Information Ontology (CHEMINF). If you want to see the potential of an integrated Semantic Web of data and services, this talk is for you.




Dr. Michel Dumontier is an Associate Professor of Bioinformatics at Carleton University in the Department of Biology, the Institute of Biochemistry and School of Computer Science. His research aims to improve our ability to represent and reason about biomedical knowledge, from experimental data to general textbook knowledge, towards building predictive systems for personalized medicine. Dr. Dumontier is an expert in developing and applying Semantic Web technologies in the biomedical and life sciences and currently serves as a co-chair for the World Wide Web Consortium Semantic Web in Health Care and Life Sciences Interest Group (W3C HCLSIG). With over 50 research publications in workshops, conferences, and journals, his innovative research is developing exciting opportunities towards pharmacogenomic based knowledge discovery.



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