Igor Jurisica, Ph.D.

Canada Research Chair in Integrative Computational Biology
University of Toronto

Igor Jurisica is a Canada Research Chair in Integrative Computational Biology, focusing on cancer research. To significantly impact cancer research, novel therapeutic approaches for targeting metastatic disease and diagnostic markers reflective of changes associated with disease onset that can detect early stage disease must be discovered. Better drugs must be rationally designed, and current drugs made more efficacious either by re-engineering or by information-based combination therapy. To tackle these complex biological problems and impact high-throughput biology requires integrative computational biology, i.e., considering multiple data types, developing and applying diverse algorithms for heterogeneous data analysis and visualization. Improved analysis and reasoning algorithms will in turn advance disease diagnosis by finding better markers, and improve patient management by supporting information-based medicine. Combined, this will 1) advance computational algorithms; 2) help to fathom cancer biology; and 3) lead to creating computational models of cancer.

Igor Jurisica is a Senior Scientist at the Ontario Cancer Institute, University Health Network, Associate Professor in the Departments of Computer Science and Medical Biophysics, University of Toronto, Adjunct Professor at the School of Computer Science, Queenès University, and a Visiting Scientist at the IBM Centre for Advanced Studies. He earned his Dipl. Ing. degree in Computer Science and Engineering from the Slovak Technical University in 1991, M.Sc. and Ph.D. in Computer Science from the University of Toronto in 1993 and 1998 respectively.

Dr. Jurisica's research focuses on integrative computational biology, and representation, analysis and visualization of high dimensional data generated by highthroughput biology experiments, in the context of Cancer Informatics. Of particular interest is the use of comparative analysis for the mining of integrated different datasets such as protein-protein interaction, gene expression profiling, and high-throughput screens for protein crystallization.
http://www.cs.toronto.edu/~juris/