Computational & Systems Biology Program
The Quaid Morris Lab
Research
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.
People
Quaid Morris, PhD
Member
- Computational biologist Quaid Morris uses artificial intelligence techniques and develops machine learning algorithms to study gene regulation, cancer evolution, clinical informatics, and other topics in systems biology.
- PhD, Massachusetts Institute of Technology
- [email protected]
- Email Address
Members
Graduate Student
Graduate Student
Postdoctoral Fellow
Computational Biologist
Graduate Student
Graduate Student
Graduate Student
Graduate Student
Graduate Student
Graduate Student
Graduate Student
Postdoctoral Fellow
Graduate Student
Senior Administrative Assistant
Postdoctoral Fellow
Graduate Student
Graduate Student
Postdoctoral Fellow
Graduate Student
Graduate Student
Graduate Student
Graduate Student
Graduate Student
Lab Alumni
Research Scientist at Autodesk AI Lab
Postdoctoral Research Fellow, Memorial Sloan Kettering Cancer Center, New York
Research Intern, Facebook AI, Pittsburgh
Research Scientist, Deep Genomics
Research Associate in Yeung Lab at SickKids, Toronto
Associate Professor, Computer Science, University of Toronto
Postdoctoral Research Fellow, Vector Institute, Toronto
Data Scientist, BioSymetrics, Toronto
Graduate Student, University of Pennsylvania
Research Scientist, Ontario Institute for Cancer Research
Postdoctoral Research Fellow, Hughes Lab, Toronto
Associate Professor, Computer Science, Antalya Bilim University
Assistant Professor, Case Western University
Software Engineer at Amazon
Graduate Student
Associate Professor, Computer Science, University of Washington; Canada CIFAR AI Chair
Graduate Student
Assistant Professor, Computer Science, University of California Davis
Research Assistant Professor in Computer Science, Stony Brook University
Research Scientist, DeepMind, London
Postdoctoral Research Fellow, Lunenfeld Research Institute, Toronto
Graduate Student
Research Scientist, Silicon Valley start-up
Founder: Argmix - A Technology Consulting Firm Specializing in Machine Learning
Research Scientist at DeepMind, London
Lab Affiliations
Achievements
- Clarivate Web of Science Highly Cited Research (2018-present)
- CIFAR Artificial Intelligence Chair (2018-present)
- Assigned RNA-binding preferences to >20% of metazoan RNA-binding proteins (and >10% of eukaryotic RBPs) (w/ Timothy Hughes)
- Developed GeneMANIA algorithm and website (w/ Gary Bader)