Experts

Dr. Hirst’s research aims to further our understanding of the role of epigenetic dysfunction in cancer initiation and progression and to translate this knowledge into improved health outcomes for Canadians. International efforts to characterize genetic lesions in cancer genomes have revealed recurrent mutations in epigenetic modifiers and in some cases these can represent the sole driver. Understanding the functional implications of these mutations, their contribution to abnormal cellular differentiation and how emerging epigenetic therapeutics may counteract their effects represent the next critical steps towards translating this knowledge. In this context, Dr. Hirst is studying cancers that harbor highly recurrent gain and loss of function mutations to epigenetic modifiers, such as acute myeloid leukemia, synovial sarcoma, malignant rhabdoid tumor. His research involves the development and application of molecular and computational tools to measure epigenetic features and drive new insights into normal and pathogenic epigenetic regulatory control.

Dr. Strömvik leads a bioinformatics research group focusing on complex polyploid genomes of plants (e.g. arctic and temperate Oxytropis sp., and potato wild relatives). She completed a Ph.D. in Crop Sciences (plant molecular genetics of soybean) at University of Illinois at Urbana-Champaign (USA), and a B.A. in Theoretical Philosophy as well as a M.Sc. in Biology (tissue culture and transformation in Picea abies) at Stockholm University (Sweden). She carried out postdoctoral studies in Bioinformatics and Computational Genomics at University of Minnesota, Minneapolis (USA) working on genomics projects in soybean, Medicago truncatula and loblolly pine. In 2003 she joined McGill’s Department of Plant Science where she pioneered the development of university-wide graduate bioinformatics programs and courses. She serves on national and international grant panels, as Associate Editor for several journals, and as Chair of the Department of Plant Science since 2015.

Dr. Mary-Ellen Harper’s research focuses on mitochondrial energetics and metabolomics – and specifically the mechanisms that impact the efficiency of energy transduction pathways in mitochondria. The research has implications for the amounts of energy ‘captured’ as ATP, and stored in cells (e.g., as lipid or glycogen), as well as for the amounts of energy released as heat. These mechanisms dictating the efficiency of energy conversion also affect oxidative stress and cell signaling. Altogether these processes in mitochondria have repercussions for metabolic health and many diseases. Experimental approaches span from molecular in vitro studies, to mouse models, and to integrative translational studies in patient populations. She and her group have published over 200 peer-reviewed papers cited over 19,300 times. Dr. Harper is the Director of the Ottawa Institute of Systems Biology (https://med.uottawa.ca/oisb/), and is also the Director of the NSERC-funded Metabolomics Advanced Training and International Exchange (MATRIX) graduate training program, based at Universities of Ottawa, McGill and Montréal http://www.matrixmetabolomics.ca. A strong proponent for the teaching and training of the next generations of scientists, she has supervised 30 HBSc, 23 MSc and 14 PhD students, as well as 12 Postdoctoral Fellows. Research is currently funded by the Canadian Institutes of Health Research (CIHR), the Natural Sciences and Engineering Research Council (NSERC); the National Research Council of Canada, Canadian Nuclear Laboratories, and Mitacs. Dr. Harper holds a University Research Chair in Mitochondrial Bioenergetics, and was recently awarded the Diabetes Canada Lifetime Achievement Award.

Matt is a member of the Animal and Poultry Science department at the University of Saskatchewan. His PhD was in Veterinary Microbiology with Dr. Janet Hill (WCVM-UofS) and MSc was in Biology with Dr. William Crosby (UWindsor). Matt has had a diverse background working on microbiome, bioinformatics and genomics projects that cover all domains of life.

Prof. Shafer previously studied the molecular mechanisms of lineage specification and stem cell division in prostate and urogenital systems (MSc Western University, PhD McGill University). During his postdoc, he transitioned into studying the genomics and evolution of brains and behaviour. At Harvard University, he developed techniques to perform comparative neurobiology with single-cell RNA-sequencing and discovered mechanisms driving cellular diversity across species in the vertebrate brain. He then moved to the University of Basel where he began work on the evolution of sleep in African Rift Lake cichlid fishes. Max is now an assistant Professor in the Department of Cell & Systems Biology at the University of Toronto.

Maxwell Libbrecht is an Assistant Professor at the School of Computing Science at Simon Fraser University. His research focuses on developing machine learning methods applied to high-throughput genomics data sets. He received his PhD in 2016 from the Computer Science and Engineering department at University of Washington, advised by Bill Noble and Jeff Bilmes, and his undergraduate degree in Computer Science from Stanford University, advised by Serafim Batzoglou. He is a 2021 Michael Smith Foundation Scholar. He was the first author of a paper named one of ISCB’s Top 10 Regulatory and Systems Genomics papers of 2015.

Dr. Mélanie Courtot’s team develops new software, databases and other necessary components to store, organize and compute over the large and complex datasets being generated by OICR’s cancer research programs. Her research focuses on new methods for improving data quality, based on knowledge representation, automated curation and added-value data of high quality for cancer related data. Dr Courtot is passionate about translational informatics – building intelligent systems to gain new insights to better predict patients’ health outcomes. Dr Courtot holds a BSc in Biochemistry and MSc in Computer science (2002) from the Université Louis Pasteur, in Strasbourg, France, and a PhD in Bioinformatics (2014) from the University of British Columbia, Canada.

Michael Brudno is a Professor in the Department of Computer Science at the University of Toronto, as well as the Chief Data Scientist at the University Health Network (UHN). He is also a faculty member at the Vector Institute for Artificial Intelligence and the Scientific Director of HPC4Health, a private computing cloud for Ontario hospitals. His main research interest is the development of computational methods for the analysis of clinical and genomic datasets, especially the capture of precise clinical data from clinicians using effective user interfaces, and its utilization in the automated analysis of genomes. This work focuses on the capture of structured phenotypic data from clinical encounters, using both refined User Interfaces, and mining of unstructured data (based on Machine Learning methodology), and the analysis of omics data (genome, transcriptome, epigenome) in the context of the structured patient phenotypes, mostly for rare diseases. His overall research goal is to enable the seamless automated analysis of patient omics data based on automatically captured information from a clinical encounter, thus streamlining clinical workflows and enabling faster and better treatments. After receiving a BA in Computer Science and History from UC Berkeley, Michael received his PhD from the Computer Science Department of Stanford University, working on algorithms for whole genome alignments. He completed a postdoctoral fellowship at UC Berkeley and was a Visiting Scientist at MIT. He is the recipient of the Ontario Early Researcher Award and the Sloan Fellowship, as well as the Outstanding Young Canadian Computer Scientist Award.

Michael Hoffman creates predictive computational models to understand interactions between genome, epigenome, and phenotype in human cancers. His influential machine learning approaches have reshaped researchers’ analysis of gene regulation. These approaches include the genome annotation method Segway, which enables simple interpretation of multivariate genomic data. He is a Senior Scientist in and Chair of the Computational Biology and Medicine Program, Princess Margaret Cancer Centre and Associate Professor in the Departments of Medical Biophysics and Computer Science, University of Toronto. He was named a CIHR New Investigator and has received several awards for his academic work, including the NIH K99/R00 Pathway to Independence Award, and the Ontario Early Researcher Award.

Michelle started her group at the Université de Sherbrooke in 2011 where she is currently a full professor in the Department of Biochemistry and Functional Genomics and a member of the RiboClub. The characterization of the snoRNome has been the main focus of her group since its beginning, including elaborating diverse tools for the study of snoRNAs and the analysis their regulation, evolution, interactions and functions. Her group is also interested in studying different aspects of the transcriptome and its deregulation in health and disease. Her group is involved in collaborations with many groups. She is funded by CIHR, NSERC, FRQNT and holds a senior professorship from the FRQS.

Our group focuses on understanding the molecular events underlying the progression of early breast lesions. We often use different types of high-throughput profiling methods to provide comprehensive molecular overviews of the lesion, its microenvironment and the patient systemic response. We also develop new methods to subject cells and tissues to multiple genetic interventions simultaneously. The profiling information is used to build computational tools to understand higher-order interactions in complex biological systems and pathways. Our goal is to develop tools for end-points with clinical relevance and to use these tools to characterize events in tumoral progression.

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.