Weill Cornell Medicine
Hartman Institute for Therapeutic Organ Regeneration
David Redmond, PhD · Assistant Professor of Computational Biology
We work at the interface of computational and wet lab biology. We run the experiments and we build the methods, and neither half is a service function for the other.
We use single-cell and spatial measurement, across transcriptome, chromatin, protein and tissue, together with functional assays at the bench, to study how transcriptional regulation sets cell identity and how immune cells and the stroma around them shape each other, in development, inflammation, ageing and regeneration.
In practice that means building atlases of cell state, working out which regulators actually set identity, and testing whether they are enough to move a cell from one state to another. We perturb systems rather than just watching them, and we check a conclusion from more than one direction, at the bench and against independent human data. A result that only holds up in cross-validation is not really a result.
Research themes
Methods and analysis frameworks for large-scale single-cell and multiomic data: atlas construction, cross-dataset integration, reproducible pipelines.
Read more →Single-cell RNA-seq, ATAC and multiome assays used together to connect chromatin state to the transcriptional programmes that define cell identity.
Read more →Methods for spatial transcriptomics and tissue imaging: mapping cell state onto tissue architecture, and quantifying vascular structure from images.
Read more →How blood vessels instruct immune and stem cells through niche signals, and how that dialogue breaks down in inflammation, infection and ageing.
Read more →Selected work
Teaching
We run two video course series on analysing sequencing data in R, one on bulk RNA-seq and GEO, one on single-cell. Both start from no programming experience. The recordings, scripts and data files are free and open to anyone.
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