Instructors
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.
Dr. Shamini Ayyadhury is the Founder and CEO of Panoramics – A Vision, a vibrant hub for collaboration, knowledge exchange, and innovation in biological topography. Under her leadership, Panoramics has grown into a nexus that brings together researchers, method developers, and innovators across the field. Panoramics organized Canada’s first two spatial biology workshops in collaboration with the Canadian Bioinformatics Workshops (CBW) and the Brain Single Cell Initiative program. She is the creative visionary behind Panoramics – A Vision and its arms – The Panoramic Chapters and the upcoming Panoramic Innovations. She is the Chair of the True North Spatial series, an initiative she originated and shaped to bring innovators together to push the boundaries of the field.
In addition, Dr. Ayyadhury is a Scientific Associate at the University Health Network (UHN) and a specialist in spatial biology, computer vision, and high-dimensional imaging analysis. She previously held a spatial biology and computer vision role at the University of Toronto as a postdoctoral fellow. Her work bridges computational method development and experimental design, combining technical depth with creative scientific leadership.
She holds a PhD in Neuroscience from McGill University, an MSc in Integrative Neuroscience from Imperial College London, and a BSc from the National University of Singapore. Her career spans institutions in Singapore, the UK, and Canada, including Nanyang Technological University, the National Neuroscience Institute, and A*STAR’s Singapore Institute for Clinical Sciences and Singapore Immunology Network. She was previously co-founder and Chief Technology Officer of Astraea Bio. She is a recognized expert and consultant in spatial biology analysis, and an emerging thought leader in the field.
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.