Research Labs

Our group, the Laboratory of Experimental Cancer Immunogenomics, is a multi-disciplinary team of cancer scientists working at the intersection of genomics, molecular genetics, animal modeling, and biostatistical data sciences.

Computational biologist Quaid Morris uses artificial intelligence techniques and develops machine learning algorithms to study gene regulation, cancer evolution, clinical informatics, and other topics in systems biology.

Cell biologist Philipp Niethammer investigates tissue damage responses with advanced imaging approaches in zebrafish.

Systems biologist Thomas Norman develops new computational and functional genomics approaches for studying how genes interact to realize complex phenotypes.

Cancer geneticist Kenneth Offit focuses on gene characterization; genetic and epidemiologic studies of cancer-predisposing alleles; and the therapeutic, prognostic, and psychosocial translation of these findings.

Led by Dr. Irene Orlow, the Lab participates in self-initiated research and supports investigations from the Population Sciences & Clinical Research programs that involving human specimens processing, testing, and banking. For additional information on current research, publications, and presentations by the Lab, and more, scroll down and click on the ‘View Lab Overview’ or ‘Current Projects’ links.

The Pavletich laboratory studies the structural biology of pathways that control cell growth and maintain the integrity of the genome.

Computational biologist Dana Pe’er combines single-cell and spatial profiling technologies with machine learning approaches to address fundamental questions in gene regulation, cellular plasticity and cell-cell communication in the contexts of cancer, immunity and development.

Molecular biologist John Petrini investigates the repair of chromosomal breaks and the activation of the DNA-damage-induced cell-cycle checkpoints.

Physician-scientist Luke R.G. Pike studies the mechanistic underpinnings of brain metastasis and seeks to identify translational correlates with outcomes following local or systemic therapy.