Quantitative biology of development and stem cells
Our lab is using a combination of experimental, computational, and theoretical approaches to quantitatively understand decision-making in single cells. We are particularly interested in how cells use gene networks to make robust decisions even in the presence of significant fluctuations in gene expression. We use and develop a wide range of single-cell methods including single-cell sequencing and quantitative imaging tools.
Keywords
Systems biology / gene regulation / noise / single-cell genomics / cellular identity