Instructors
Dr. Simpson develops algorithms and software for the analysis of high-throughput sequencing data. He is interested in de novo assembly, the detection of sequence variation in individuals, cancers and populations and the application of compressed data structures to large analysis problems. Dr. Simpson developed the ABYSS and SGA software packages.
Jasmine received her Bachelor’s degree in Biology, majoring in Molecular Biology and minoring in Marine Biology, from the University of New Brunswick in April 2013. She then pursued her Master’s degree in Epidemiology from the Department of Epidemiology, Biostatistics and Occupational Health from McGill University in May 2016. Her research interest is integrating microbiome and metabolomics data to gain deep functional insights.
His research focuses on statistics and bioinformatics for metabolomics, microarray and next generation sequencing (RNA-seq) data analysis and integration. Some of the tools he developed in the past include MetaboAnalyst for statistical analysis of metabolomics data, MSEA for metabolite set enrichment analysis, MetPA for metabolic pathway analysis, ROCCET for ROC curve based biomarker analysis, and NetworkAnalyst for data integration and network analysis. His general interest is high-throughput omics data analysis using a variety of statistics, machine learning and data visualization technologies.
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.
I am a principal investigator of computational biology at the Ontario Institute of Cancer Research (OICR) and associate professor at University of Toronto (UofT) at the departments of Medical Biophysics and Molecular Genetics. I completed a PhD in computer science at the University of Tartu in Estonia in 2010 and postdoctoral training at the Donnelly Centre (UofT) during 2011-2015. I started my lab at OICR and the faculty appointment in 2015. I am interested in computational biology, machine learning, and cancer research
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.
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.