A Workshop on Deep Learning for CryoEM
Participants discussed applications of deep learning to problems of interest to cryoEM. These included particle picking, selection of appropriate 2D classes, decisions on the numbers of 3D maps, segmentation of tomograms, etc.
The goal of this workshop was to bring together machine learning experts and cryoEM practitioners to discuss the use of deep learning methods to applications in cryoEM.
The Agenda is below. The workshop was webcast to YouTube and then content available here. PDF versions of slides that have been made available by the speakers can be found by following the links attached to the speakers’s names in the agenda below.
A Workshop on Deep Learning for CryoEMs
10 April 2018
9:00 am Welcome and Introductions Clint Potter and Bridget Carragher
9:30 am Convolutional Neural Networks for Tomogram Segmentation and Particle Picking Steve Ludtke
9:30 am Deep Learning Based Structural Pattern Mining in Cellular Electron Cryo Tomograms Min Xu
10:30 am Break
11:00 am Utilizing deep learning for cellular cryo-tomography Neils Volkmann
11:30 am Automatic particle picking with minimal supervision using neural networks Tristan Bepler
12:00 pm APPLE Picking: Particles without Templates Joakim Andén
12:30 pm Lunch
1:30 pm Iterative Non-Uniform Refinement David Fleet
2:00 pm Getting started with Differentiable Programming in Cryo-EM Dmitry Tegunov
2:30 pm Failure modes in deep learning application to CryoEM data Muyuan Chen
3:00 pm Break
3:30 pm Denoising Cryo-EM data with Conditional Generative Adversarial Networks Michael Cianfrocco
4:00 pm Panel Diuscussion