Data Analytics & Genomics for Precision Medicine
I'm a biologist with a computational and statistical background, and an interest in advancing clinical
decision-making from patient data (precision medicine). In January 2021, I started my research group at the Ontario
Institute for Cancer Research.
During the COVID-19 pandemic I've been active in public health advocacy.
Keywords: precision medicine; machine learning; genomics; epigenetics; statistics; method development; software; covid-19 advocacy; science outreach; maps
As part of my postdoctoral research, I led the project to build netDx, an algorithm that builds a patient classifier by integrating several types of user-provided data. It outperforms most machine-learning methods in binary cancer survival prediction. It has some nice properties for clinical research, including the ability to handle sparse and missing data, and grouping genes into pathways for interpretability.
Read our methods paper here, and about the general strategy we use (patient simiilarity networks), in this review I co-wrote with Dr Bader. netDx is publicly available as R software. My work and collaboration for netDx was honoured with the 2019 Donnelly Centre Research Excellence award.
I am also interested in understanding how epigenetic factors - particularly DNA methylation - contribute to increase risk for brain-related disorders (read this review I co-wrote for motivation). I co-led the first genome-wide comparison of DNA methylation in neurons isolated from post-mortem brains of individuals with psychosis vs undiagnosed individuals. Funded partly by a 2014 NARSAD Young Investigator award to myself, in this work we discovered a new method for dopamine regulation in neurons.
Read our research article here: Pai et al. (2019) Nat Comms 10. This research was covered by various media outlets (Altmetric score of 134, as of April 2021 - top 5% of all scored research outputs by Altmetric).
Research publications are listed on Google Scholar.
I am lead developer on patient classifier netDx, available on github and Dockerhub. I have contributed software packages for genome viz to R/Bioconductor project. My github repo contains repositories associated with research articles. As a graduate student working on animal neuroscience, I designed and implemented Matlab code to automate adaptive multi-step animal training protocols ("SessionModel"). That code and its successors are in use in numerous cognitive neuroscience labs at Cold Spring Harbor Labs and Princeton U, in the US.
I created and lead the Canada COVID-19 School tracker, an
to highlight the full impact of COVID-19 on Canadian schools and to advocate for safe school policies.
Our team of 13 volunteers maps and tracks cases and outbreaks in
schools. We are active on social media and have advocated
schools in several media outlets across Canada and US.
This project is an initiative through my volunteer work with grassroots advocacy group Masks4Canada.
During the Canadian PPE shortage in the Spring, I volunteered with The
to sew cloth face masks for community groups.
Communities served: Michael Garron Hospital Mask Drive, March of Dimes, Homes First, Sunnybrook Hospital.
|2004||B.Math. Hon. Computer Science
University of Waterloo, ON, Canada
|2010||Ph.D. Biological Sciences
Cold Spring Harbor Laboratory, NY, USA
|2010 - 2014||Postdoctoral Fellow
Centre for Addiction & Mental Health, Toronto, Canada
Epigenetics (PI: Art Petronis, MD PhD)
|2015 - 2020||Postdoctoral Fellow
The Donnelly Centre, University of Toronto
Computational methods for precision medicine
(PI: Gary Bader, PhD)
I'm on Twitter and rarely on LinkedIn, but am reliably reachable by e-mail to firstname.lastname@example.org.