Photo of Michel Dumontier

Michel Dumontier

Adjunct Research Professor

Degrees:Ph.D. (Toronto)

Current Research

Our research aims to better understand how living systems respond to chemical agents. A key aspect of our approach involves using computational frameworks that are powered by formal (i.e. machine understandable) semantics to make effectively use of vast and diverse amounts of biomedical knowledge. We are particularly interested in understanding how the response to chemical exposure is modulated by genetic and physiological variation among individuals and how this translates into altered capabilities at the molecular level. 

Selected Publications

Ayvaz S, Horn J, Hassanzadeh O, Zhu Q, Stan J, Tatonetti NP, Vilar S, Brochhausen M, Samwald M, Rastegar-Mojarad M, Dumontier M, Boyce RD. Toward a complete dataset of drug-drug interaction information from publicly available sources. J Biomed Inform. 2015 Jun;55:206-17.

Samwald, M., Gimenez, J. A., Boyce, R. D., Freimuth, R. R., Adlassnig, K., Dumontier, M. Pharmacogenomic knowledge representation, reasoning and genome-based clinical decision support based on OWL 2 DL ontologies. BMC Medical Informatics and Decision Making. 2015; 15.

Callahan, A., Cifuentes, J. J., Dumontier, M. An evidence-based approach to identify aging-related genes in Caenorhabditis elegans. BMC Bioinformatics.  2015; 16.

Hoehndorf, R., Hiebert, T., Hardy, N. W., Schofield, P. N., Gkoutos, G. V., Dumontier, M. Mouse model phenotypes provide information about human drug targets. Bioinformatics.  2014; 30 (5): 719-725.

Callahan A, Cruz-Toledo J, and Dumontier M. Bio2RDF Release 2: Improved coverage, interoperability and provenance of Life Science Linked Data. 2013. Lecture Notes in Computer Science. 7882:200-212.