This course aims to teach learners about high throughput, high-performance algorithms for high-resolution subtomogram averaging in cryo-electron tomography. The learning outcomes include understanding the importance of data processing throughput and processing time in obtaining high-resolution reconstructions, as well as gaining knowledge about tools like TomoBEAR and SUSAN for in situ structural biology. The course covers topics such as sample purification workflow, substack analysis, CTF estimation, and 3D reconstruction. The intended audience for this course includes researchers, scientists, and professionals in the field of structural biology and cryo-electron microscopy.
High Throughput, High Performance Algorithms for High Resolution Subtomogram Averaging
Institute for Pure & Applied Mathematics (IPAM) via YouTube
Overview
Syllabus
Intro
Structures of membrane proteins
Excitation-contraction coupling in skeletal muscle
Sample purification workflow
Structure of RyR1 in native membranes
Structure of RyR1 at the resolution of secondary structure
Comparison to the other reported structures of RyR1
Subtomogram averaging is successful for a class of molecules
Throughput considerations
More options for particle picking with user assistance
Benchmarking tomoBEAR
Optimizing subtomogram averaging
Substack analysis with SUSAN
CTF estimation module in SUSAN - "normalization"
CTF estimation module in SUSAN - "linearization"
3D reconstruction in SUSAN
Benchmarking SUSAN
Conclusions and outlook
Taught by
Institute for Pure & Applied Mathematics (IPAM)
