People
Kay is a Professor in the School of Computing Science at Simon Fraser University, Canada. His research interests are in RNA structure prediction, RNA visualization, CRISPR-Cas sgRNA design and other related applications. He enjoys developing innovative machine learning and optimization techniques for practical applications, but he is also interested in studying and developing new fundamental machine learning approaches. One such problem is developing neural networks that adapt their activation functions based on the underlying task. His lab developed the RnaPredict software for RNA folding, the jViz.RNA package for RNA visualization including pseudoknots, and the EvoDNN software for self-adaptive deep neural networks.
Keegan (she/her/hers) is an assistant professor in the Department of Statistics at the University of British Columbia and an investigator in the Centre for Molecular Medicine and Therapeutics at the BC Children’s Hospital Research Institute. She is also a faculty member in the Bioinformatics and Genome Science and Technology graduate programs at UBC. Her research group tackles the challenging task of uncovering meaningful biological insights from large-scale genomic experiments. Innovative technologies now allow scientists to probe the genome in more dimensions and at higher resolution than ever before, providing a wealth of information for studying the genomic basis of complex traits. However, discoveries from these new technologies can often be masked by technical artifacts, systematic biases, or low signal-to-noise ratio – think “needle in a haystack”. Keegan leads a team of researchers that focuses on developing novel frameworks and rigorous inferential procedures that exploit the increased scope and scale of high-throughput sequencing data, with the ultimate goal of uncovering new molecular signals in cancer, child health, and development.
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.
Khanh Dao Duc got his PhD in applied mathematics in 2013 from the Ecole Normale Superieure (Paris, France) under the supervision of Dr. David Holcman, and did his postdoctoral training with Professor Yun Song at UC Berkeley and UPenn from 2014 to 2019. He joined UBC in 2019 as an assistant professor in Mathematics and associate member in Computer Science, where he runs an interdisciplinary group that develops theoretical and computational methods and tools for analyzing biological data and study various biological processes across biological scales. Recent works include computational methods for Cryo-EM, database and web application for ribosome structures, pipeline to analyze Ribo-seq data, cell shape analysis and algorithm from AFM and fluorescence image data, ML methods for interpreting electronic health records.
Kieran received his BSc from the University of Edinburgh in Mathematical Physics followed by a masters in Computational Biology at Cambridge University and a DPhil (PhD) in statistical genomics at Oxford University. He was subsequently a Banting postdoctoral fellow at the University of British Columbia and BC Cancer Agency (2017-2019). He is now Principal Investigator & Scientist at the Lunenfeld-Tanenbaum Research Institute, an Assistant Professor in the Departments of Molecular Genetics and Statistical Sciences, University of Toronto, and affiliate faculty at the Ontario Institute for Cancer Research.
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.