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Sara Geraghty

Department: Lewis-Sigler Institute for Integrative Genomics
Faculty Adviser: Mona Singh
Year of Study: G3
Undergraduate School: University of Richmond
Undergraduate Major: Biology and Computer Science

Personal Bio

Hello! I’m Sara, a third-year graduate student in the Quantitative and Computational Biology doctoral program at Princeton. Though I grew up nearby in Freehold, NJ, I did my undergrad at the University of Richmond in VA, where I double majored in biology and computer science. Though I now focus primarily on cancer genomics and human disease, at UR I did independent research on the evolution of animal symbioses using freshwater sponges and their symbiotic algae as a model system. Outside of research, I am an outdoor enthusiast and love hiking, kayaking, and camping, am a budding home cook and breadmaker, paint and draw, and am a proud cat mom.

Fun Fact

I love to travel and have been to forty US states and ten countries! One of my favorite parts is trying all the food along the way, so I would be happy to talk about food with my mentee - ideally while eating some too 😊

Research Pitch

My research combines knowledge and techniques from cancer biology, genetics, mathematics, and machine learning to try and understand molecular mechanisms of cancer. Essentially, it asks: given that we have an abundance of sequencing data from cancer patients, how can we harness that data to create useful computational models (i.e. those that can shed light on what is going on inside cancer cells, compared to normal cells?). More specifically, the models I’m developing aim to predict how genetic mutations and copy number alterations alter the transcriptional and epigenetic landscape of the cancer genome. We are doing this across 33 different cancer types from The Cancer Genome Atlas. My current work is computational and mostly involves writing algorithms and handling large datasets in Python and R (though we’d ultimately like to experimentally validate our models, too!).

Plans for Summer 2022

Confirmed pairing; no longer looking for a mentee.

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