Jurisica, Igor

Biography

Merely coping with the deluge of data is no longer an option; their systematic analysis is a necessity in biomedical research. Computational biology is concerned with developing and using techniques from computer science, informatics, mathematics, and statistics to solve biological problems. Analyzing biomedical data requires robust approaches that deal with high dimensionality, multi-modal and rapidly evolving representations, missing information, ambiguity and uncertainty, noise, and incompleteness of domain theories. Our research is focussed on integrative computational biology, and representation, analysis and visualization of high dimensional data generated by high-throughput 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. We integrate multiple data sources and database, develop and apply combination of diverse algorithms in a systematic manner. Besides performance, our focus is on scalable algorithms with easy use by non-experts. Merely coping with the deluge of data is no longer an option; their systematic analysis is a necessity in biomedical research. Computational biology is concerned with developing and using techniques from computer science, informatics, mathematics, and statistics to solve biological problems. Analyzing biomedical data requires robust approaches that deal with high dimensionality, multi-modal and rapidly evolving representations, missing information, ambiguity and uncertainty, noise, and incompleteness of domain theories. Our research is focussed on integrative computational biology, and representation, analysis and visualization of high dimensional data generated by high-throughput 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. We integrate multiple data sources and database, develop and apply combination of diverse algorithms in a systematic manner. Besides performance, our focus is on scalable algorithms with easy use by non-experts.

Research Interest

Cellular and Molecular Biology; Cancer Biology