Synthetic cellular imaging uncovers invisible phenotypes
Biology, as an experimental science, heavily relies on observations. However, despite humongous progress in our ability to see and quantify biological events thanks to techniques such as super resolution microscopy, mass spectrometry or single cell sequencing, many processes and phenotypes remain out of reach, inaccessible. This is the case for instance for subtle phenotypic alterations that are hidden by biological or experimental cell variability. In this talk, I will relate research projects from our lab where synthetic imaging based on biophysical modeling or deep learning can be used to explain and even quantify subtle phenotypes, invisible to the human eye. I will illustrate the usefulness of these general approaches in the context of basic research in neuroscience and drug discovery.
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