Our Work

Quantitative Cell Science

The maps we need

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Diseases are caused by disruptions in the inner workings of cells or in the communication between cells. That’s why we support rigorous, quantitative research in cell biology and developmental biology, showing how healthy cells work and, more importantly, what takes place when disease strikes.

Malfunctioning cells are at the root of many human diseases, including cardiovascular disease, neurodegeneration, diabetes, and cancer. Our goals are to map and understand cellular physiology across scales in time and space and to make the data we obtain openly available to advance all research in cell biology. Understanding the healthy cell is a prerequisite to diagnosing, understanding, and treating the diseased state.


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Intracellular Architecture

Manuel Leonetti‘s, team brings together cell biologists, data scientists, and engineers to build a reference map of how the human cell is internally organized. Their flagship project, OpenCell, is combining CRISPR engineering, live-cell microscopy, and proteomics to characterize the spatial location and molecular interactions of all the proteins that make up the cell.

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Organismal Architecture

Using state-of-the-art, custom-built light-sheet microscopes coupled with spatial transcriptomics and photoactivation of lineage-specific reporters, Loïc Royer and his group are mapping how tissues form during early development at unprecedented spatial and temporal resolution. These studies are enabled by innovative tools for machine learning, image analysis, refinement, and visualization.

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Physical Biology and Biophysical Theory

Led by Greg Huber, a group of mathematicians and computational and theoretical physicists is working in close collaboration with experimental biologists, using tools from applied mathematics and theoretical physics to understand problems in cell biology and beyond.

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Quantitative Tissue Morphogenesis

Adrian Jacobo’s group uses a combination of zebrafish transgenesis, cutting-edge imaging tools, and mathematical modeling to understand how tissue architecture emerges from the spatial and temporal dynamics of cell–cell signaling.