Biophysics Seminar

Friday, 12 May, 10:00, DCHB Phase 2 Seminar Room (20-138)
Talk 1
Deep learning for data synthesis in fluorescence microscopy 
Dr Susan Cox, King’s College London



In cryo-EM synthesis of information from multiple views is well established as a method for inferring molecular structure. We have developed a way to extend this technique to the mesoscale using fluorescence microscopy images of multiple views of a single structure as inputs, with deep learning accelerating the fit of the angle of each view. Using this approach, we are able to perform completely free fits and reproduce nanoscale structure.

Talk 2
Effector release from synthetic tissues induces patterned gene expression in bacterial populations
Jorin Riexinger, University of Oxford



Synthetic cells can communicate with living cells through a range of mechanisms, such as the controlled release of proteins to drive neural differentiation or light-activatable synthesis of IV-HSL to induce gene expression in bacterial cells. However, these systems are limited in that cellular responses cannot be controlled spatially. Here, we describe the interaction between 3D-printed synthetic tissues and living cells by patterned release of effector molecules for the purpose of spatially defined gene expression. Additionally, a key-lock mechanism is proposed in which the combination of two functionally different synthetic tissues induce gene expression at any desired point in time.