Education
Bio
Dr. Wishart currently supervises over 40 students, staff and post-doctoral fellows. Since 1990 he has published more than 300 papers and presented over 300 posters/abstracts. He has delivered more than 300 invited lectures all over the world on a variety of topics, including cutting edge bioinformatics tools, drug design, metabolomics, precision medicine, general sequence analysis, gene finding, protein annotation, protein structure analysis, structure prediction, biomedical text mining, cellular simulation, nanobot design and synthetic biology. He is responsible for the creation of metabolomics databases in Edmonton that receive over 20 million hits a year, thus making Edmonton the centre of the world's most influential metabolomics databases. He has developed automated metabolomics profiling software that reduces data processing time by up to 90%. He has also help to pioneer many of the necessary technical, software and database developments to enable metabolomics to enter the scientific mainstream. Dr. Wishart is also the Director of The Metabolomics Innovation Centre (TMIC), which is Canada's national metabolomics platform. He has been cited over 40,000 times and is an inventor on several patents.
Areas
Algorithmics
Bioinformatics
Database Systems
Machine Learning
Interests
Bioinformatics, analytical chemistry, simulations, computational biology, structural biology.
Summary
Dr. Wishart's formal training is in physics, biochemistry, biophysics, pharmaceutical science and computational biology. His research interests lie in:
Selected Industry Collaborations and Commercialization
OMx Personal Health Analytics
Introduction to computational tools and databases used in the collection and analysis of sequence data and other analytical data from high-throughput molecular biology studies. Students will use existing tools, and learn the underlying algorithms and their limitations. Prerequisite: any 200-level Biological Sciences course or consent of instructor. Credit cannot be obtained for both BIOIN 301 and BIOL 501.
Fall Term 2022Advanced topics in bioinformatics will be covered. A major part of the course will be devoted to team-based projects involving writing novel bioinformatics tools to deal with current problems in bioinformatics. Prerequisites: BIOIN 301, a 300-level CMPUT course and a 300-level GENET course. (Offered jointly by the Departments of Computing Science and Biological Sciences). [Biological Sciences].
Winter Term 2023Discussion of computational tools and databases used in the analysis of data from high-throughput molecular biology studies. Students will use existing tools, learn the underlying algorithms and their limitations, and will be required to complete an individual research project. Prerequisite: consent of instructor. Credit cannot be obtained for both BIOIN 301 and BIOL 501.
Fall Term 2022