Instructors
Dr John Parkinson is a computational biologist whose research interests focus on the impact of microbiota on human health. After completing his PhD at the University of Manchester, studying molecular self-assembly, John spent a year at the University of Manitoba investigating diatom morphogenesis. In 1997, John moved to Edinburgh where he applied computer models to study the evolution of complement control proteins with Dr Paul Barlow. With the emergence of high throughput sequencing, John then led the bioinformatics efforts associated with the parasitic nematode expressed sequence tag project, responsible for the processing and curation of sequence data from 30 species of parasitic nematodes. John was recruited to the Hospital for Sick Children in 2003 and was promoted to Senior Scientist in 2009. He holds cross-appointments in both the departments of Biochemsitry and Molecular Genetics at the University of Toronto. Current lab interests center on the role of the microbiome in health and disease as well as the mechanisms that allow pathogens and parasites to survive and persist in their human hosts. Key to this research is the integration of computational systems biology analyses with comparative genomics to explore the evolution and operation of microbial pathways driving pathogenesis. Findings from our research programs are helping guide new strategies for therapeutic intervention.
Julia is a MSc student in the Department of Medical Biophysics at the University of Toronto. She is interested in developing and evaluating computational frameworks for biomarker discovery and clinical validation to advance precision oncology. Her current research focuses on identifying new (epi)genomic biomarkers that predict treatment response in breast cancer.
Dr. Jüri Reimand is a principal investigator at the Ontario Institute for Cancer Research (OICR) and associate professor at the University of Toronto, Canada. His lab focuses on computational biology, cancer genomics, and development of statistical and machine-learning methods. Areas of interest include interpretation of the non-coding genome and driver mutations, integrative analysis of multi-omics data through pathway and network information, and discovery of molecular biomarkers.
Kelsy is a PhD candidate in the Molecular Cell Biology program at Washington University in St. Louis. She completed her undergraduate degree at Mercer University in 2016, where she earned a B.S. in Biochemistry and Molecular Biology. She is interested in developing methods to analyze multiple types of sequencing data in order to better understand regulatory mutations and splicing within cancer, particularly with respect to personalized cancer vaccine design. Currently, she is involved with [2]DGIdb, [3]RegTools, ORegAnno and analysis of several breast cancer clinical cohorts. She is also part of the Precision Medicine Pathway and Cancer Biology Pathway at WashU, which allows to better understand how she can translate genomics and informatics into the clinic more efficiently.
Laura Hug seeks to define microbial diversity and function at contaminated sites using culture-based and culture-independent methods, generating a blueprint of which species are there and which pathways are active.
Her research expands our understanding of the tree of life, while simultaneously developing solutions to address the impacts of human activities on the environment.
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.
Dr. Lawrence Heisler manages the Genome Sequencing Informatics Analysis team as part of the Genomics Program at OICR. His team develops analysis workflows and production pipelines in support of clinically accredited and research-use only sequencing assays. He holds a graduate degree in Physiology from Queen’s University in Kingston Ontario, and has over 20 years of experience with analysis of genomic data.
Letícia is a PhD candidate at Dalhousie University, investigating the genotype-phenotype evolution of whale acoustics. Her research combines genomics, bioinformatics and bioacoustics to understand how whales adapted their communication to different environments. Letícia is also active in teaching, science communication and outreach. She is the developer and instructor of the undergraduate course “Science Communication for Social Change” at Dalhousie, runs a bilingual science communication page (@leticiamagpali) and the outreach program “Evolution for Everyone”, which offers free training in bioinformatics to equity-seeking students.
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.
Dr. Linglong Kong is a Professor in the Department of Mathematical and Statistical Sciences at the University of Alberta, holding a Canada Research Chair in Statistical Learning and a Canada CIFAR AI Chair. He is a Fellow of the American Statistical Association (ASA) and the Alberta Machine Intelligence Institute (Amii), with over 120 peer-reviewed publications in leading journals and conferences such as AOS, JASA, JRSSB, NeurIPS, ICML, and ICLR. Dr. Kong received the 2025 CRM-SSC Prize for outstanding research in Canada. He serves as Associate Editor for several top journals, including JASA and AOAS, and has held leadership roles within the ASA and the Statistical Society of Canada. Dr. Kong’s research interests include high-dimensional and neuroimaging data analysis, statistical machine learning, robust statistics, quantile regression, trustworthy machine learning, and artificial intelligence for smart health.