b'Pursuing ourobjectivesThe Genomics Technology Platforms supported are: The Proteomics Centre, Victoria, British Columbia BC Cancer Agency Genome Sciences Centre, Vancouver, British Columbia The Metabolomics Innovation Centre, Calgary, Alberta The Centre for Applied Genomics, Toronto, Ontario Network Biology Collaborative Centre, Toronto, Ontario Canadian Data Integration Centre, Toronto, Ontario McGill University and Genome Quebec Innovation Centre, Montreal, Quebec Centre for Advanced Proteomic and Chemogenic Analyses, Montreal, Quebec Canadian Centre for Computational Genomics, Montreal Quebec and Toronto, Ontarioin seven projects (described here). These projects included cut-ting-edge projects like the one led by Dr. David Juncker at McGill University to develop techniques to analyze single exosomestiny droplets secreted by cells that can be used as fingerprints for cancer cells, with the potential to transform the cancer diag-nostics market.Genomics is being transformed by enormous quantities of data available through increased sequencing activity, creating op-portunities and challenges in the area of bioinformatics and computational biology. This year, Genome Canada awarded a total of $23.1 million to 25 projects in the Bioinformatics and Computational Biology competition, designed to produce next-generation tools and technologies to take advantage of these large data sets (project descriptions provided here). A project led by Dr. Paul Stothard at the University of Alberta and Dr. Gary van Domselaar of the Public Health Agency of Canada are de-veloping software that will allow non-bioinformatics researchers to convert raw bacterial sequence data into high-quality, richly described, and easily interpreted whole-genome assemblies that will be much more easy to apply to their research programs. Dr. Leonid Chindelevitch and Dr. Maxwell Libbrecht of Simon Fraser University are collaborating with Jesse Shapiro of the University of Montreal to develop computational tools based on artificial intelligence and machine learning, which will be able to unravel the complex relationships between bacterial genome sequences and antibiotic resistance.Genome Canada Annual Report 2018-19 21'