Our group combines computational and experimental techniques to study the cellular organization of complex tissues, with a focus on determining the phenotypic diversity and clinical significance of tumor cell subsets. Although our research cuts across disciplinary boundaries, we specialize in the development of robust computational strategies to address key questions in the cancer genomics field, with an emphasis on clinical translation of our findings into novel biomarkers and individualized therapies. As a member of the Department of Biomedical Data Science and the Institute for Stem Cell Biology and Regenerative Medicine, and as an affiliate of graduate programs in Biomedical Informatics, Cancer Biology, and Immunology, we are also interested in the development of impactful biomedical data science tools in areas beyond our immediate research focus, including developmental biology, regenerative medicine, and systems immunology.
- Computatonal Biology
- Cancer Genomics
- Stem Cell Bioinformatics
- Machine/ Statistical Learning