Instructors

Lauren has an MSc in Biostatistics from the University of Toronto and has previously worked as a Biostatician for two pediatric psychiatric genetics labs at SickKids. She is currently an MSc student in Dr. Anna Goldenberg’s lab. In her work, Lauren is focused on developing and applying statistical machine learning methods primarily in the area of data integration for improved translational discovery in the fields of genetics and genome biology. Lauren has also created custom R programming and data analysis courseware and taught over 200 trainees and scientists in the SickKids research program.

Prior to joining OICR in 2006, Dr. Stein played an integral role in many large-scale data initiatives at Cold Spring Harbor Laboratory and at the Massachusetts Institute of Technology (MIT) Genome Center. He led the development of the first physical clone map of the human genome, and ran the data coordinating centre and the data portal for the SNP Consortium and the HapMap Consortium. Dr. Stein has also led the creation and development of Wormbase, a community model organism database for C. elegans, and Reactome, which is now the largest open community database of biological reactions and pathways. At OICR, Dr. Stein has led several international cancer data sharing and research initiatives, including the creation and development of the data coordination centre for the International Cancer Genome Consortium and other related projects. He continues to collaborate with national and international partners to create and promote data sharing standards, protocols and implementations.

Lusine received her Ph.D. in Mathematics under the supervision of prof. V. Bogachev from Moscow State University in the area of nonlinear stochastic equations for measures. She works in Dr. D. Wishart’s computational group, where she learned machine learning and Python and developed tools for applications in bioinformatics. She also works in research involving applications of EPR spectroscopy at the Applied Pharmaceutical Innovation.

Mai obtained Ph.D. in Chemical Biology from McMaster University in 2019. Her Ph.D. research focused on metabolomics of irritable bowel syndrome and inflammatory bowel disease. Later, she worked as a postdoc under Dr. Jeff Xia at McGill University and became more familiar with R programming and computational work in the field of metabolomics. Currently, she works under Dr. David Wishart to make metabolomics-based personalized health assessment more accessible in partnership with an industrial partner.

Dr. Griffith’s research is focused on the development of genomics and bioinformatics methods as they apply to the study of cancer biology and medicine. A particular focus of his work is in the translation of genomics data from whole genome, exome and transcriptome sequencing into clinically actionable observations and personalized cancer therapies. He has led the development of key online informatics resources for cancer precision medicine such DGIdb, DoCM, CIViC and more.

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).

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.