Instructors

Our lab uses machine learning and artificial intelligence to do biomedical research, focusing on cancer evolution, gene regulation, clinical informatics, and gene function prediction. A key interest is the role of RNA-binding proteins (RBPs) in post-transcriptional regulation. We focus on developing computational and experimental techniques to determine the RNA specificities of RBPs (both sequence and structural) and use these specificities to predict their target transcripts, determine RBP function, and ultimately decipher the regulatory code. Another focus is reconstructing and modelling somatic evolution (pre- and post-cancer) using bulk and single-cell genomic data. In general, we are focused on using large, heterogeneous functional genomic datasets to uncover insights about gene function. Recently, we have becoming increasingly interested in using artificial intelligence and predictive analytics, along with electronic medical records, to inform patient care, particularly in the domain of auto-immune disease.

Richard has been involved in the implementation and use of high-throughput sequencing analysis pipelines for genomic and transcriptome data sets. Currently, he is developing tools for the analysis of SARS-CoV-2.

Rob (or “Dr. Robert Beiko”, if you want to be all formal about it) is an Associate Professor in Bioinformatics in the Faculty of Computer Science at Dalhousie University. Before coming to Dal in 2006, he was a postdoc in the lab of Mark Ragan at the University of Queensland in Brisbane, Australia. And before that, he completed a PhD in Biology at the University of Ottawa (1998-2003). Although all of his formal training was in biology, an interest in machine-learning approaches, algorithms for identifying important evolutionary events, and visualization of biological data have ultimately led him to put down stakes in Computer Science and collaborate with some of the best in the business here.

After completing a postdoctoral position in Australia, Rob joins the team as a Bioinformatics consultant specializing in fungal/plant genetics and developing omics resources, strategies, and infrastructure for laboratories working with non-model organisms. He has more than a decade of experience working in genomics, and holds a PhD in bioinformatics from Curtin University.

Robin is a microbiologist with experience in bioinformatics, curation and outreach. Dr. Haw has a PhD in genetics and was a senior curator at Biomolecular Interaction Network Database (BIND) and managing curator at Science Signaling’s Signal Transduction Knowledge Environment (STKE). He has been responsible for coordinating outreach, Reactome presentations and training at workshops and conferences.

Ruiyan is a PhD candidate in the Department of Medical Biophysics at the University of Toronto. Graduated with a Bachelor’s degree in Biomedical Engineering from the Hong Kong Polytechnic University, she is interested in applying advanced deep learning techniques to medical image classification and segmentation in radiotherapy. Her current research focuses on automatic segmentation of targets and organs-at-risk in cervical brachytherapy using deep learning.

Bioinformatician and data analyst in the Bader lab applying pathway and data analysis to varied data types. Developed Enrichment Map App for Cytoscape, an app to visually translate functional enrichment results from popular enrichment tools like GSEA to networks. Further developed the Enrichment Map Pipeline including development of additional Apps to help summarize and analyze resulting Enrichment Maps, including PostAnalysis, WordCloud, and AutoAnnotate App.

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!