CellPheΒΆ
Welcome to CellPhe, a multidisciplinary research initiative focused on redefining how we understand and quantify the dynamic life of cells. By combining high-throughput time-lapse microscopy with automated machine learning, we move beyond static snapshots to capture the dynamic phenotype of individual cells. Our mission is to bridge the gap between complex imaging data and actionable biological insights, enabling researchers to predict cell fate, identify heterogeneous subpopulations, and accelerate discoveries in areas ranging from drug resistance to cancer dormancy. Whether you are looking for open-source tools like our CellPhe R package and CellPhePy Python toolkit, or seeking to collaborate on cutting-edge bioimaging research, we invite you to explore our resources and join us in decoding the complexities of cellular behavior.
