Due to both the underlying combinatorial nature of biological processes and the vast increase in data-generation capacity of modern biological lab techniques, the fields of biology and computer science are rapidly becoming inextricably linked. The Bioinformatics lab aims to bridge the gap in expertise between these two disciplines and develop computational techniques for solving biological problems, particularly as they apply to health- and agriculture-related fields.

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The Bioinformatics lab has a steady stream of publications in leading journals such as Bioinformatics, BMC Bioinformatics, Nature Communications, Nature Plants, and PLoS ONE. In addition, they have close partnerships with researchers at the Vaccine and Infectious Disease Organization (VIDO), Agri-Food Canada, Global Institute for Food Security (GIFS), College of Medicine, College of Agriculture and Bioresources, and Western College of Veterinary Medicine in order to directly apply their research in the fields of agriculture, disease, and health.

• Improved techniques for normalizing and analyzing data from kinome micro-arrays.
• Developing diagnostic tests using portable, inexpensive genomic sequencing technologies.
• Developing algorithms for analyzing transposable genomic elements.
• Computational techniques to determine the 3D organization of chromosomes in a nucleus using interaction data.
• Machine learning techniques to predict genomic features that are predictive of microbial resistance in pathogens.
• Computational methods to identify novel microRNA-drug interactions with application to drug repositioning and drug discovery.
• Machine learning approaches to finding associations between genomic features and plant phenotypes.
• Component-based phenotyping of plants and inference of developmental plant models.
• Prediction of polyploid genome evolution and ancestral genome construction.

• Dr. Tony Kusalik
• Dr. Ian McQuillan
• Dr. Lingling Jin
• Dr. Matthew Links (Associate)
• Dr. Fangxiang Wu (Associate)