Instructors
He graduated with Ph.D in Informatics from University of Missouri-Columbia in December 2019. His current work focusses on understanding Acute Myeloid Leukemia at the single cell level using Single cell RNA-sequencing analysis. He is interested in developing informatics approaches in Single cell RNA-seq to better understand Cancer.
I am currently the NGS sequencing core Manager/Research Investigator and member of the McCombie lab at Cold Spring Harbor Laboratory. I work in developing and adapting new technologies for Next-Generation sequencing routines and other applications. During my time here I have developed optimizations for the Pacific Biosciences RS instrument for large genome sequencing, evaluated rational pooling schemes for large cohort sequencing on Ilumina platforms, and I have developed applications for sequencing and error corrections on the Oxford Nanopore MinIon. Currently I am using optical mapping strategies to evaluation long structural variants in in cancer lines and Oxford Nanopore for CNV detection in clinical samples.
I am an Associate Professor at the Paul Allen School of Computer Science and Engineering at University of Washington (UW).
Before joining UW, I was an Assistant Professor at the Department of Statistics and the Department of Medical Genetics at University of British Columbia (UBC), and a faculty member at the Vector Institute. I also held a Canada Research Chair (CRC II) in Computational Biology (2015-2020), and a Canada CIFAR Chair in Artificial Intelligence (CIFAR-AI).
Before joining UBC, I did my postdoctoral fellowship with Daphne Koller at Stanford University. I got my PhD in Computer Science from the University of Toronto in 2011, working with Quaid Morris. My PhD thesis was on integrating large-scale genomics and proteomics datasets to predict gene function. Check out GeneMANIA to find out more about this project!
Sejin is a PhD Candidate at the University of Toronto working on applying deep learning models for personalized prognostication of head and neck cancer patients. As the lead developer of Med-ImageTools, an open-source Python package for processing medical images, he is determined to make sure his research is easily reproducible and accessible for the wider scientific community to increase clinical adoption of machine learning methods and ultimately improve patient outcomes.
Postdoctoral Fellow, UofT/UHN
Senior Data Scientist, Pathomics.io
Director, Panoramics – A Vision
Dr. Shamini Ayyadhury is a computational postdoctoral fellow at the University of Toronto and University Health Network, applying and developing various computational pipelines, which includes computer vision and AI methodologies, for spatial and single cell transcriptomic and image datasets. She is the Director of Panoramics – A Vision, a pan-Canadian spatial and single cell working cluster bringing spatial and single cell scientists together for scientific debate, education and discussion.
The Pai Lab at OICR analyzes high-throughput multi-omic data in the healthy developing and adult brain, and in pediatric and adult brain cancer, to identify diagnostic and prognostic biomarkers for eventual clinical implementation. We work with data from genome sequencing technologies at single-cell resolution (e.g., scRNAseq) and bulk tissue (e.g., RNAseq, WGBS, EMseq, ChIPseq), with sample sizes ranging to cohort-scale. We specialize in understanding the role of the non-coding genome in disease progression.
Dr. Sorana Morrissy completed her PhD in Medical Genetics at the University of British Columbia, Vancouver, BC, under the supervision of Dr. Marco Marra. She pursued post-doctoral research in translational genomics in Dr. Michael Taylor’s lab at the Hospital of Sick Children in Toronto, ON. Throughout her training she gained extensive experience with cutting-edge high-throughput sequencing technologies and computational analyses in the field of cancer research, with a particular focus on understanding tumor heterogeneity and recurrent disease.
Dr. Tallulah Andrews is an Assistant Professor in the Department of Biochemistry at the University of Western Ontario. Her group focuses on the integration of biological imaging and multiple -omics technologies to understand the structure of diseased tissues. She is a long-term member of the Human Cell Atlas developing computational tools for single-cell RNAseq data while a post-doc at the Wellcome Sanger Institute in Cambridge, UK and analyzing the Healthy Liver atlas in the MacParland group at UHN Research. She holds a PhD from the University of Oxford where she used systems biology approaches to identify biological pathways underlying rare genetic diseases.
Dr. Trevor Pugh is a Senior Investigator and the Director of Genomics at OICR. He leads the OICR Genomics program, which brings together the Princess Margaret Genomics Centre, OICR’s Genome Research Platform, Translational Genomics Laboratory and Genome Sequence Informatics teams under an integrated initiative to support basic, translational and clinical research.
Dr. Vasu Gautam is the senior scientist and Bioinformatics Manager at Wishart Node, University of Alberta. Vasu is intrigued by the diverse world of “omics” and their combined role in biological research, be it proteomics, genomics, or metabolomics. Vasu has worked in both academia and industry in the field of multi-omics. His interest has been to explore the different aspects of these “omics” groups and then combine this knowledge pool to address some of the most difficult questions in the field. Bioinformatics/computational biology has been a great tool in enhancing this capability and continuing his research. His current focus is the study of machine learning algorithms and their applications in different areas of metabolomics.
Vicki is a PhD Candidate at the University of Toronto studying invasive species in the subarctic, from the tundra to the boreal forest, and the effect of climate change and anthropogenic disturbances on invasive species at high latitude. In addition to doing summer fieldwork and analyzing those data, she also teaches “Quantitative Methods in R for Biology”, a third-year undergrad statistics course, and has taught and assisted dozens of workshops to students with a wide range of coding and statistics knowledge.