Research topics: We study variation across populations to understand human health and disease, using genomic and proteomic data.
Techniques: We develop and apply computational systems biology approaches based on statistical/machine learning methods for integrating and analyzing large datasets.
Seeking undergrads for: Academic year, Summer
Required skills: Programming experience - Students should have some familiarity in programming in a commonly used language for data analysis - typically R or Python or equivalent.
This lab is particularly interested in mentoring: Undergrads from backgrounds that are underrepresented in STEM, Undergrads without previous exposure to laboratory research
How to apply: Contact Dr. Gentles (email@example.com)
Project information: One potential research project is investigating connections between cancer and Alzheimer disease using public datasets. We also have projects leveraging single cell RNAseq to analyze glioblastoma. However, other project areas are open for discussion.