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Dr Michel Dumontier
Assistant Professor
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CTTC4610 1125 Colonel By Drive Ottawa, Ontario K1S 5B6 |
Education and Research
| Rank: | Assistant Professor |
| Degrees: | Ph.D. University of Toronto (2004) |
| Research Interests: | Bioinformatics, Computer Graphics, Database Systems, Hardware, Logic Programming, Medical Computing, Parallel Computing, Particle Simulation, Personalized Medicine, Reasoning, Semantic Web for Biological Data Integration, Systems Biology, and Web Technologies |
Biography
Dr. Michel Dumontier has a strong interest in realizing the potential of interdisciplinary research from the areas of medicine, molecular and cell biology, biochemistry, organic chemistry, computational biology, computer science and engineering. After his second year of undergraduate study in Biochemistry at the University of Manitoba, he joined the group of Dr. Jim Jamieson and Dr. Gro Thorne-Tjomsland in investigating enzymatic glycobiology and developing 3D models of the rat hepatocyte Golgi apparatus from serial section electron micrographs. After graduating in 1998 with a Bachelor of Science in Biochemistry, Dr. Dumontier worked as a research associate at the Max Planck Institute for Biochemistry in Munich, Germany where he researched Rac1A actin-cytoskeleton reorganization and signalling in the slime mold Dictyostelium discoideum. Dr. Dumontier earned his Doctor of Philosophy in 2004 from the University of Toronto with advisor Christopher Hogue by developing computational scoring functions based on species-specific optimizations of sequence and structure optimizations across 150 completely sequenced organisms. His work has implications for taxonomic identification, sequence alignment, secondary structure and protein structure prediction. During his post-doc at the Blueprint Initiative (2004-2005) he developed SMID-Genomes, an early drug discovery tool that allows the comparison of predicted small molecule binding profiles based on structural interactions. Since July 2005, Dr. Dumontier leads his research group at Carleton University towards personalized medicine using computational drug discovery and cell simulation.
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