Geeleher Lab

About the Geeleher Lab

We develop scalable computational methods for single-cell and spatial genomics and integrate patient tumors with large-scale CRISPR and pharmacological screens. We use these analyses to identify and experimentally validate drug targets, biomarkers and therapeutic combinations, with a particular focus on neuroblastoma and pediatric solid tumors.

The Team

The Geeleher Lab has a hybrid team of computational biologists and bench scientists tackling cutting edge problems in translational medicine.

Meet the Team

Our research summary

Single-cell and spatial genomics

We develop machine-learning / AI methods that recover biological programs and cellular states from atlas-scale single-cell and spatial datasets. Our work emphasizes scalability, reproducibility and the interpretation of complex tumor ecosystems.

Connecting patient tumors to experimental models

We compare the cellular and molecular states found in patient tumors with those represented in cell lines, organoids and patient-derived xenografts. This allows us to determine which experimental models are appropriate for studying particular tumor states and therapeutic vulnerabilities.

Functional genomics and combination discovery

We integrate CRISPR perturbation screens, pharmacological profiling and genomic data to identify drug targets, biomarkers and rational therapeutic combinations.

Experimental and translational validation

Our experimental group investigates the most promising computationally nominated vulnerabilities using molecular, cellular and in vivo approaches, with an emphasis on neuroblastoma and other pediatric solid tumors.