People
Mira is a principal research officer and team led at the Digital Technologies RC and Adjunct Professor in Biochemistry, Microbiology and Immunology at University of Ottawa. Her main interests are in the application of ML and data mining life sciences with particular interest in metabolomics and lipidomics and applications in the diseases of aging and neurodegeneration. She was involved in the development of bioinformatics solutions (made available through https://complimet.ca) as well as utilization of computational biology for biomarker discovery and simulation of biological systems.
Mohamed is a Computational Systems Biologist and Principal Scientist leading the Bioinformatics and Systems Biology Lab (BSBL) at the Vaccine and Infectious Disease Organization (VIDO), University of Saskatchewan. He received his MSc and PhD in Computational Systems Biology from Keio University (Tokyo, Japan) and completed his postdoctoral training in bioinformatics at Kyoto University and the University of Toronto. Mohamed’s interdisciplinary research profile bridges biology, computer science, and public health.
The focus of Dr. Langille’s research is to better understand human-microbial interactions and how that can be used to improve human health. This includes leveraging novel genomic technologies and developing improved bioinformatic methods to process and integrate multi-omic data to aid in biological interpretation. These discoveries will hopefully lead to novel applications for diagnosis and therapeutics.
Nadia Tahiri received her M.Sc. and Ph.D. degrees in Computer Science from the University of Quebec at Montreal. She is currently an Assistant Professor in the Department of Computer Science at the University of Sherbrooke. Her research interests include evolution, phylogenetic tree, clustering, classification, computational biology, and biogeography, and consensus tree/supertree.
Nicholas Provart is a professor of plant cyberinfrastructure and systems biology and is chair of the Department of Cell & Systems Biology at the University of Toronto. Currently his Bio-Analytic Resource (BAR) at bar.utoronto.ca, comprising tools for coexpression analysis of publicly-available gene expression data, cis-element prediction, identifying molecular markers, generating “electronic fluorescent pictographic” (eFP) representations of gene expression patterns, and exploring protein-protein interactions in Arabidopsis and other plants, receives 4M page views a month by researchers worldwide. He is one of the founding members of the International Arabidopsis Informatics Consortium, is president of the Multinational Arabidopsis Steering Committee, and is teaching five MOOCs on bioinformatic methods, plant bioinformatics, and data visualization for genome biology on Coursera.org.
Nikta is a PhD student in the Medical Biophysics program at the University of Toronto. She completed her Bachelor of Science in Microbiology and her Master of Science in Bioinformatics. For her MSc thesis, Nikta worked on developing supervised algorithms for classifying cancer-specific somatic mutations. Her research interests include application of machine learning algorithms in pharmacogenomic analysis, cancer diagnosis and personalized medicine.
The goal of Professor Basu’s research is to design, validate, and apply innovative and sustainable approaches (focused on toxicogenomics) to address the most pressing societal concerns over toxic chemicals in our environment. Professor Basu’s research is multidisciplinary (bridges environmental quality and human health), inter-sectoral (most projects driven by stakeholder needs, notably government and communities), and driven by environmental justice concerns.
Dr. Griffith’s research is focused on the development of personalized medicine strategies for cancer using genomic technologies. He develops and uses bioinformatics, machine learning and clinical statistics for the analysis of high throughput sequence data and identification of biomarkers for diagnostic, prognostic and drug response prediction. He has led the development of key online informatics resources such as DGIdb, CIViC, GenVisR and more.
Patrick McMillan is a PhD candidate studying bioinformatics at the University of Guelph. His research looks at how to better model the interaction between a crop’s genotype and the environment in which it’s grown. Patrick completed his M.Sc. in Applied Statistics where he studied how to model the effects of surface mining on aquatic ecosystems in the Athabasca Oil Sands region in Alberta.
I received a PhD in biomolecular modelling from University College London, researched protein folding and genomics at UCSF and Yale, and am currently a professor of computational biology, focusing on development of techniques to analyze low-complexity and intrinsically disordered proteins, and prions.