Hi, I’m Cait

cait headshot

I am a graduate student at the University of Toronto supervised by Quaid Morris and Kieran Campbell, and a graduate researcher at the Vector Institute and Ontario Institute for Cancer Research. I use machine learning to understand cancer evolution.

I did my undergraduate studies at the University of Toronto, in Computational Biology and Statistics. I’m passionate about open science, and promoting great mentorship in the sciences.

I like to drink coffee and go hiking ☕ 🏔️ ☀️

Office Hours

As part of my ongoing commitment to supporting students at all levels and background in engaging with ML and computational biology, I make an effort to be available to provide mentorship, guidance, and resources.

I set aside ~2h/month for by-request 30 minute meetings, which you can book online, or reach out to me by email to arrange times outside of those listed.


* Indicates equal contribution

Peer Reviewed Publications

Regional Mutational Signature Activities in Cancer Genomes

Caitlin Timmons, Quaid Morris, and Caitlin F. Harrigan

PLOS Computational Biology, 2022

Activating mTOR mutations are detrimental in nutrient-poor conditions

Agata A. Bielska, Caitlin F. Harrigan, Yeon Ju Kyung, Quaid Morris, Wilhelm Palm, and Craig B. Thompson

Cancer Research, 2022

Reconstructing evolutionary trajectories of mutation signature activities in cancer using TrackSig

Yulia Rubanova, Ruian Shi, Caitlin F. Harrigan, Roujia Li, Jeff Wintersinger, Nil Sahin, Amit Deshwar, and Quaid Morris

Nature Communications, 2020

TrackSigFreq: subclonal reconstructions based on mutation signatures and allele frequencies

Caitlin F. Harrigan, Yulia Rubanova, Quaid Morris, and Alina Selega

Pacific Symposium on Biocomputing, 2020

Other Publications

Whole slide Imaging Mass Cytometry allows the rapid profiling of the immune landscape of histopathologically aggressive prostate tumors

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, Hartland W. Jackson

AACR annual meeting proceedings, 2024

Bacterial ADP-heptose initiates a revival stem cell program in the intestinal epithelium

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

biorxiv, 2024

Considerations for Visualizing Uncertainty in Clinical Machine Learning Models

Caitlin F. Harrigan*, Gabriella Morgenshtern*, Anna Goldenberg, and Fanny Chevalier

Workshop paper at CHI 2021


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


TrackSigFreq: subclonal reconstructions based on mutation signatures and allele frequencies

Machine Learning in Computational Biology



Academic Talks

Mutational Signatures for DNA Damage and Misrepair

BIRS: Mathematical Methods in Cancer Biology, Evolution and Therapy

Invited talk

05/23 view

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

03/23 view code

Data Collection & Analysis

PRISM research & mentorship program, University of Toronto

Invited by Prof. Sadia Sharmin

02/22 pdf

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

03/24 pdf

Finding the ‘I’ in science

ACM Canadian Celebration of  Women in Computing

Selected Workshop

10/22 pdf

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



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

06/23 - 08/23 view

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

09/22 - 12/22 view

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.

05/21 - 08/22 view

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

05/20 - 11/20 view

Teaching Assistant Positions

JSC370: Data Science II

01/23 - 05/23

JSC270: Data Science I

01/23 - 05/23

STA313: Data Visualization

09/22 - 12/22

PRISM: Preparation for Research through Immersion, Skills, and Mentorship

01/22 - 05/22

JSC370: Data Science II

01/22 - 05/22

CSC197: Privacy in the Age of Big Data Collection

09/21 - 12/21

STA4273: Minimizing Expectations

01/21 - 05/21

CSC197: Privacy in the Age of Big Data Collection

09/20 - 12/20

JSC270: Data Science I

01/20 - 05/20

CSC373: Algorithm Design, Analysis & Complexity

09/19 - 12/19


“I was fortunate to work with Cait for almost a year and had a wonderful experience. She was patient, supportive, and skilled at explaining complicated concepts in biology and programming. As a mentor, she has a great sense of when to guide you through a problem and when to let you work through challenges on your own. She helped me grow as a researcher and writer and I’m grateful for everything I learned from her.”

“As a mentor, Caitlin has greatly enhanced my ability to conduct research. She also provided valuable resources and aimed to make sure that I understood the fundamental concepts behind all the research conducted by breaking down difficult principles into easily comprehensible statements and thoughts. Additionally, she helped me find any sources of error as the research progressed. I enjoyed researching under her guidance, and I had an overall positive experience.”