My PhD research focused on modeling oncogenic fusion genes involving transcription factors to understand how they drive ultra rare cancers. As a PhD candidate in Ross Okimoto’s lab at UCSF, I built models to dissect the biology of fusions defined by rearrangement of the transcriptional repressor capicua (CIC).

For my postdoc I joined the Schmidt Science Fellows community to explore my interest in synthetic biology within the context of plants, where I hope to build approaches to leverage transcription factors as tools for engineering phenotypes in cells. I am pursuing this work in Jenn Brophy’s lab at Stanford.

During my PhD, my favorite wet lab technique was cloning (the creativity is addictive), while one of my ever-present side projects was to be a better fluorescent microscopist (see: photography as a hobby).

I strongly believe in researchers being fluent in both generating data and processing it. To this end, I mainly use R and bash scripting to work with anything from IHC staining scores to raw NGS data.

I’ve used or taken classes in IDL, Java, Python, R, and bash scripting, including a fully computational rotation in the lab of Dr. Marina Sirota in my first year at UCSF. In the fall of 2022 I was exceptionally fortunate to take the Advanced Sequencing Technologies & Bioinformatics Analysis course at Cold Spring Harbor Laboratory, which helped to train me in full-pipeline processing of NGS data. During my PhD I was the acting bioinformatician for the Okimoto lab, and helped not just our own lab members but also collaborators with data analysis.

My favorite R functions are pivot_longer and pivot_wider (from tidyr, they always seem like magic), while my least favorite kind of bioinformatic data analysis is gene ontology analysis (I rarely find it informative & would rather just read the gene list manually).