Cait Harrigan, MSc.
Cait Harrigan, MSc.
cait.harrigan@mail.utoronto.ca | View this CV online at caitharrigan.ca/cv
I am a graduate student at the University of Toronto supervised by Quaid Morris and Kieran Campbell. I’m a graduate researcher at the Vector Institute and Doctoral Fellow at the UofT Data Sciences Institute. I use machine learning to understand cancer genomics by modelling the evolutionary constraints that underlie how mutations occur in DNA. I’m passionate about open science, and promoting great mentorship in the sciences.
Education
PhD in Computer Science, University of Toronto
Supervised by Quaid Morris and Kieran Campbell
MSc. in Computer Science, University of Toronto
Supervised by Quaid Morris
BSc. in Computational Biology, University of Toronto
Awarded with distinction
Research experience
Visiting Graduate Researcher
The Francis Crick Institute, London, England
Hosted by Nicholas McGranahan
Visiting Graduate Researcher
Memorial Sloan Kettering Cancer Center, New York, USA
Hosted by Quaid Morris
Visiting Graduate Researcher
Memorial Sloan Kettering Cancer Center, New York, USA
Hosted by Quaid Morris
Undergraduate Research Assistant
SickKids Hospital, Toronto, Canada
Supervised by Michael Wilson and Anna Goldenberg
Peer Reviewed Publications
* Indicates equal contribution
- Caitlin Timmons, Quaid Morris, and Caitlin F. Harrigan. “Regional mutational signature activities in cancer genomes”. En. In: PLOS Computational Biology 18.12 (Dec. 2022), p. e1010733.
- Agata A. Bielska, Caitlin F. Harrigan, Yeon Ju Kyung, Quaid Morris, Wilhelm Palm, and Craig B. Thompson. “Activating mTOR mutations are detrimental in nutrient-poor conditions”. Eng. In: Cancer Research (Jul. 2022).
- Caitlin F. Harrigan, Yulia Rubanova, Quaid Morris, and Alina Selega. “TrackSigFreq : subclonal reconstructions based on mutation signatures and allele frequencies”. In: Pacific Symposium on Biocomputing 25 (Jan. 2020), pp. 238-249.
- Yulia Rubanova, Ruian Shi, Caitlin F. Harrigan, Roujia Li, Jeff Wintersinger, Nil Sahin, Amit Deshwar, and Quaid Morris. “Reconstructing evolutionary trajectories of mutation signature activities in cancer using TrackSig”. In: Nature Communications 11.1 (Feb. 2020), pp. 1-12.
Other Publications
- Caitlin F. Harrigan, Gabriela Morgenshtern, Anna Goldenberg, and Fanny Chevalier. “Considerations for Visualizing Uncertainty in Clinical Machine Learning Models”. Oct. 2022.
- Jennifer L. Gorman, Lydia Y. Liu, Jordan P. Hartig, Nikesh Parsotam, Amanda Khoo, Vladimir Ignatchenko, Sarah Asbury, Somi Afiuni, Ricardo Gonzalez, Michael J. Geuenich, Caitlin F. Harrigan, Yuju Lee, Jianan Chen, Liang Lim, Qanber Raza, Peggi M. Angel, Kieran Campbell, Stanley K. Liu, Michelle R. Downes, Richard R. Drake, Thomas Kislinger, David King, and Hartland W. Jackson. “Abstract 5561: Whole slide Imaging Mass Cytometry allows the rapid profiling of the immune landscape of histopathologically aggressive prostate tumors”. In: Cancer Research 84.6_Supplement (Mar. 2024), p. 5561.
- Shawn Goyal, Cynthia X. Guo, Adrienne Ranger, Derek K. Tsang, Ojas Singh, Caitlin F. Harrigan, Olga Zaslaver, Hannes L. Rost, Herbert Y. Gaisano, Scott A. Yuzwa, Nan Gao, Jeffrey L. Wrana, Dana J. Philpott, Scott D. Gray-Owen, and Stephen E. Girardin. “Bacterial ADP-heptose initiates a revival stem cell program in the intestinal epithelium”. En. Jan. 2024.
- Caitlin F. Harrigan, Gabriella Morgenshtern, Anna Goldenberg, and Fanny Chevalier. “Considerations for Visualizing Uncertainty in Clinical Machine Learning Models”. Realizing AI in Healthcare: Challenges Appearing in the Wild, Workshop at CHI 2021 Online Virtual Conference, May. 2021.
Posters
SignaTree: Mapping the Evolution of Mutational Signatures on Tumour Phylogenies
ISMB 2024
Dirichlet allocation of mutations to model DDR in cancer
Toronto DNA Damage & Repair Symposium
Dirichlet Allocation of Mutations Captures the Action of DNA Damage and Misrepair Processes
Intelligent Systems for Molecular Biology
Dirichlet Allocation of Mutations in Cancer Genomes
Machine Learning in Computational Biology
TrackSigFreq: subclonal reconstructions based on mutation signatures and allele frequencies
Machine Learning in Computational Biology
Fellowships & Awards
Mitacs Graduate Research Award
Mitacs, in partnership with UKRI
NSERC Postgraduate Scholarship - Doctoral
University of Toronto
DSI Doctoral Student Fellowship Award
Data Science Institute, University of Toronto
Queen Elizabeth II Graduate Scholarship in Science & Technology
(respectfully declined)
Ontario Graduate Scholarship
Department of Computer Science, University of Toronto
ACM SIGHPC Computational & Data Science Fellowship
Special Interest Group on High Performance Computing of the Association for Computing Machinery
JXTX foundation Genome Informatics Scholarship
James P. Taylor Foundation for Open Science
General Motors Women in Science and Mathematics Award
University of Toronto
Academic Talks
Mutational Signatures for DNA Damage and Misrepair
BIRS: Mathematical Methods in Cancer Biology, Evolution and Therapy
Invited talk
DAMUTA: Dirichlet allocation of mutations as a function of both damage and DNA repair
Cold Spring Harbour Laboratory Meeting: Genome Informatics
Selected Talk
TrackSigFreq: subclonal reconstructions based on mutation signatures and allele frequencies
Pacific Symposium on Biocomputing
Selected Talk, Poster
Guest Lectures
Exploring & Explaining Data in the Wild
AI & Data Science Post-Graduate Program, Loyalist College
Invited by Prof. Peter Papadakos as an anual guest lecturer in 2023 & 2024
Data Collection & Analysis
PRISM research & mentorship program, University of Toronto
Invited by Prof. Sadia Sharmin
Environmental & Life Sciences Workshop Series
STEMHub Foundation
Invited workshop series
R for bioinformatics
Global Society for Genetics and Genome Biology
Invited workshop
Other Talks
Machine Learning for Cancer Genomics
Artificial Intelligence in Healthcare Society Case Competition, York University
Invited keynote
Finding the ‘I’ in science
ACM Canadian Celebration of Women in Computing
Selected Workshop
Undergraduate research opportunities: how to find them and make them work for you
UofT Bioinformatics and Computational Biology Student Union
Invited by the BCBSU
How to hack your degree
Computer Science Student Union, University of Toronto
Invited by the CSSU
Service
Research Mentorship
Kiki Zhang
Combined BS/MSE Student; Biomedical Engineering. Research internship via Computational Biology Student Program at MSKCC.
Topic: Mutational signatures in the context of branching evolution
Fedir Zhydok
BS Student; Computer Science. Course project in Artificial Intelligence in Medicine “global classroom” program at University of Toronto.
Topic: Identifying metastatic tumours from mutational signatures
Caitlin Timmons
BA Student; Statistical and Datasciences, Biology. Research internship via Computational Biology Student Program at MSKCC. Went on to a Research Technician position at Dana-Farber Cancer Institute.
Topic: Modelling spatial distribution of mutational signatures in cancer genomes.
Haritha Lakshmanan
Highschool Student. Independent study at MSKCC. Went on to a combined BA/MD at Brooklyn College.
Topic: Automatic discovery of mutations predictive of survival in breast cancer patients
Progam Administration
Program Organizer
UofT Graduate Application Assistance Program, Toronto
Project Manager
STEMHub Foundation, Toronto, Canada
Founder and treasurer
Bioinformatics and Computational Biology Student Union, University of Toronto
Event chair
Bioinformatics and Computational Biology Hackathon, University of Toronto
Communications and Marketing Executive
UofT Women in Computer Science (WiCS), University of Toronto
Teaching Assistant Positions
Unless otherwise noted, school is University of Toronto
JSC370: Data Science II
JSC270: Data Science I
STA313: Data Visualization
PRISM: Preparation for Research through Immersion, Skills, and Mentorship
JSC370: Data Science II
CSC197: Privacy in the Age of Big Data Collection
STA4273: Minimizing Expectations
CSC197: Privacy in the Age of Big Data Collection
JSC270: Data Science I
CSC373: Algorithm Design, Analysis & Complexity
Mentorship
As part of my ongoing commitment to supporting students at all levels and background in engaging with computational biology, I make an effort to be available to provide guidance and resources to students, with a particular focus on creating an inclusive environment that fosters diverse perspectives and experiences. In addition to being a mentor through the organized programs listed here, I set aside ~2h/month for by-request 30 minute meetings.
Computer Science Alumni Mentorship Program
Statistical Science Alumni Mentorship Program
ProjectX machine learning research competition
Her Code Camp, Toronto Ontario
Department of Statistics Mentorship Program
SPROUT Peer Mentorship Program
New College E-Mentorship Program