scholarly journals Towards on-the-fly Cryo-Electron Microscopy Data Processing by High Performance Data Analysis

2018 ◽  
Vol 955 ◽  
pp. 012005 ◽  
Author(s):  
Evgeny Pichkur ◽  
Timur Baimukhametov ◽  
Anton Teslyuk ◽  
Anton Orekhov ◽  
Roman Kamyshinsky ◽  
...  
Keyword(s):  
Electron Microscopy ◽  
Data Analysis ◽  
Data Processing ◽  
High Performance ◽  
Performance Data ◽  
Cryo Electron Microscopy ◽  
Electron Microscopy Data ◽  
Microscopy Data

scholarly journals Atomic-accuracy models from 4.5-Å cryo-electron microscopy data with density-guided iterative local refinement

2015 ◽  
Vol 12 (4) ◽  
pp. 361-365 ◽  
Author(s):  
Frank DiMaio ◽  
Yifan Song ◽  
Xueming Li ◽  
Matthias J Brunner ◽  
Chunfu Xu ◽  
...  
Keyword(s):  
Electron Microscopy ◽  
Local Refinement ◽  
Cryo Electron Microscopy ◽  
Electron Microscopy Data ◽  
Microscopy Data

scholarly journals Low cost, high performance processing of single particle cryo-electron microscopy data in the cloud

2015 ◽  
Author(s):  
Michael A. Cianfrocco ◽  
Andres E. Leschziner
Keyword(s):  
Electron Microscopy ◽  
Single Particle ◽  
High Performance ◽  
Low Cost ◽  
Cost Effective ◽  
Cryo Electron Microscopy ◽  
Software Packages ◽  
Electron Microscopes ◽  
Microscopy Data ◽  
New Generation

The advent of a new generation of electron microscopes and direct electron detectors has realized the potential of single particle cryo-electron microscopy (cryo-EM) as a technique to generate high-resolution structures. However, calculating these structures requires high performance computing clusters, a resource that may be limiting to many likely cryo-EM users. To address this limitation and facilitate the spread of cryo-EM, we developed a publicly available ‘off-the-shelf’ computing environment on Amazon’s elastic cloud computing infrastructure. This environment provides users with single particle cryo-EM software packages and the ability to create computing clusters that can range in size from 16 to 480+ CPUs. Importantly, these computing clusters are also cost-effective, as we illustrate here by determining a near-atomic resolution structure of the 80S yeast ribosome for $28.89 USD in ~10 hours.

scholarly journals EMDA: A Python package for Electron Microscopy Data Analysis

2021 ◽  
pp. 107826
Author(s):  
Rangana Warshamanage ◽  
Keitaro Yamashita ◽  
Garib N. Murshudov
Keyword(s):  
Electron Microscopy ◽  
Data Analysis ◽  
Electron Microscopy Data ◽  
Microscopy Data ◽  
Python Package
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