Computational & Systems Biology Program
The Kushal Dey Lab
Research
Kushal Dey, PhD
Nominating candidate risk genes and gene sets underlying disease-critical processes is of utmost importance for developing drug targets and informing CRISPR screening. The Kushal Dey Lab focuses on developing machine learning models and computational pipelines that integrate genomic and epigenomic data from RNA-seq, ChiP-seq, Perturb-seq experiments with genetic association studies (GWAS, WES) to enhance our understanding of the functional architecture of all heritable complex diseases, including immune-related diseases like Alzheimers’, IBD, Lupus and several heritable cancers like Breast and Prostate cancers.
Some of the research directions of interest include developing:
- Models to prioritizing variants, genes and cell states for disease using a combination of genetic, genomic and perturbation data.
- Models to identify the causal directed graphs underlying gene and gene interaction models for disease.
- Benchmarking pipelines informed by disease genetics to validate and compare different genomic prediction models.
People
Kushal Dey, PhD
- The Kushal Dey Lab builds computational models that integrate genetic and genomic data to prioritize variants, genes, and cell types, and to decode the causal functional architecture underlying heritable complex diseases — including immune-related diseases, like Alzheimer’s and inflammatory bowel disease, and heritable cancers, like breast cancer.
Lab Affiliations
Achievements
- Josie Robertson Investigator (2023–2028)
- K99/R00 Pathway to Independence Award (NIH/NHGRI) (2022–2026)
- University of Chicago Arts, Science + Culture Graduate Collaboration Grant (2017–2018)
- David Wallace Award for Applied Statistics, University of Chicago (2016)