Inference Poses for Reconstruction of 3D Molecular Volumes from Cryo-EM Images
Institute for Pure & Applied Mathematics (IPAM) via YouTube
Build with Azure OpenAI, Copilot Studio & Agentic Frameworks — Microsoft Certified
Learn AI, Data Science & Business — Earn Certificates That Get You Hired
Overview
Build a Learning Habit
Download Class Central's free printable study calendar
Download for Free
Explore a 46-minute lecture on advanced techniques in cryo-electron microscopy (cryo-EM) reconstruction presented by Frederick Poitevin from SLAC National Accelerator Laboratory. Delve into the challenges of processing large cryo-EM datasets and learn about cryoAI, an innovative ab initio algorithm for homogeneous reconstruction. Discover how this approach combines a learned encoder for particle image pose prediction with a physics-based decoder to create neural representations of scattering potential volumes. Gain insights into the potential of this inference method for handling arbitrarily large datasets and its implications for structural biology research.
Syllabus
Frederick Poitevin - Inference Poses for Reconstruction of 3D Molecular Volumes from Cryo-EM Images
Taught by
Institute for Pure & Applied Mathematics (IPAM)