Instructors

He received a Ph.D. in Biochemistry from the University of Missouri-Columbia, USA, in 2002, where he studied the structure and dynamics of oncoviral proteins with high-resolution NMR methods. Mark conducted his post-doctoral research of protein structural biology in University of Michigan, USA, and then joined Dr. Wishart’s group at University of Alberta, Canada, to work on data analysis and software development in the fields of metabolomics, NMR, and protein structure and dynamics.

Mark Phillips works in comparative privacy and data protection law, particularly where it intersects with health data sharing. His academic background is in law and computer science, and he is a practicing member of the Quebec Bar Association. He works at the Centre of Genomics and Policy at McGill University as an Academic Associate, and is the co-chair of the Data Protection Task Team of the Global Alliance for Genomics and Health’s Research and Ethics Work Stream. His comparative legal research focuses on topics including cloud computing, the identifiability of personal data, bioinformatics, and open data.

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.

As a Bioinformatics manager of the TechDev unit, Mathieu ensures the integration and the support of new genomics technologies in the platform and he leads the software development. Prior to joining C3G, Mathieu was the team leader of the Bioinformatics service unit at Genome Quebec. He holds a PhD in Statistical Genetics from University Paris-Sud XI and a Master degree in Genetics from University Pierre-et-Marie-Currie (Paris VI).

Melanie is a registered Medical Laboratory Technologist and member of CMLTO in good standing. She has over 25 years of experience in Histology; 3 years in diagnostic Histology (Dynacare and Mount Sinai) and was team lead for the Pathology research program at UHN for 22 years. She has recently changed roles and has returned to Mount Sinai as Laboratory Manager for Mount Sinai Services.

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.

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.

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.