Alice Y
- Research Program Mentor
PhD candidate at Stanford University
Expertise
bioinformatics, machine learning, cancer, drug discovery, drug development, translational science, startup, academia
Bio
With a background in biomedical data science, Alice is driven by a passion for developing computational tools that address complex biological challenges. She has created methods to map cell-to-cell communication networks, enabling the discovery of novel drug targets, and has advanced tools that accelerate drug design with the goal of expediting clinical translation. Her experience spans both academic and biotech settings, where she has led cross-functional teams at the intersection of machine learning and biotechnology. Outside of work, she loves communicating science in accessible ways— whether through social media content, blog posts, or mentoring students from high school to PhD level. In her downtime, you can find her exploring new hiking trails or cooking up a new batch of jam.Project ideas
Unravelling Drug Side Effects with Single-Cell Perturbation Analysis
This project aims to uncover potential side effects of a drug by analyzing single-cell RNA sequencing (scRNA-seq) data from treated samples compared to healthy controls. While drug mechanisms are often well understood, side effects—especially those emerging in specific cell types or due to off-target gene regulation—remain difficult to predict. scRNA-seq provides the resolution to detect these subtle, cell-type-specific transcriptomic shifts. By examining how gene expression patterns and biological pathways change in response to the drug, the project will address key questions: Which genes are altered and can these transcriptomic signatures be linked to known or novel clinical side effects? How can we adapt this to wide-scale toxicity testing to enable safer drug development?