David Redmond, Ph.D., Assistant Professor of Computational Biology Research in Medicine
Dr. David Redmond uses single-cell methods, imaging technologies, and machine learning to address questions of identity, fate, and heterogeneity in cell biology.
By using recent technologies including massive parallel single-cell RNA-sequencing, we can ask fundamental questions with an emphasis on both reprogramming and the vascular niche, such as: How do endothelial and hematopoietic cells develop and specify themselves? What drives and explains the resulting massive diversity of endothelial cell types and how they interact with surrounding cells?
This also has multiple applications to medically-oriented questions such as: How do blood vessels go awry in disease? What are the consequences of endothelial cell heterogeneity and how do they interact with the immune system? Can we leverage the vascular-immune interactions to gain a better understanding of the tumor microenvironment and show when and why cancer treatments such as chemotherapy or immunotherapy work?