Analysis of neurodegenerative diseases progression, at a single cell level, with Deep Neural Networks (360G-Wellcome-205970_Z_17_Z)

The aim of the project is to investigate neurodegenerative diseases, by determining novel neuronal cell phenotypes, classify them and to develop a step wise neurodegenerative diseaseprogression map. Stem cells differentiation technology allows scientists to access neurons involved in pathology of various neurodegenerative disease, however, there is big gap in good methods to investigate diseases at the single cell level. Thus, I will imagine organelles of iPSC derived neurons at a super-resolution level with 3D-SIM. Cellular heterogeneity will be investigated with the deep neural networks (DNN), which can detect numerous phenotypes of neurons and classify them into various heath states, this will allow us to produce a step wise disease progression map for PD and FTD in vitro models. Key goals:Goal 1: Develop and train DNN to detect cellular phenotypes (University of Oxford);Goal 2: Develop neurodegenerative disease progression map (University of Oxford)Goal 3: Understand why DNN grouped neurons into the particular classes (NIH);Goal 4: Undertake CRISPRi screens and DNN will be used as a readout (NIH).This project could set a scene for developing novel analysis methods for neurodegenerative diseases, it can produce a step wise disease progression map and reveal novel interventiontargets.