CryoPoseNet: End-to-End Simultaneous Learning of Single-particle Orientation and 3D Map Reconstruction from Cryo-electron Microscopy Data

Author(s):  
Youssef S. G. Nashed ◽  
Frederic Poitevin ◽  
Harshit Gupta ◽  
Geoffrey Woollard ◽  
Michael Kagan ◽  
...  
2020 ◽  
Vol 60 (5) ◽  
pp. 2561-2569 ◽  
Author(s):  
Andreas D. Schenk ◽  
Simone Cavadini ◽  
Nicolas H. Thomä ◽  
Christel Genoud

2018 ◽  
Vol 955 ◽  
pp. 012005 ◽  
Author(s):  
Evgeny Pichkur ◽  
Timur Baimukhametov ◽  
Anton Teslyuk ◽  
Anton Orekhov ◽  
Roman Kamyshinsky ◽  
...  

2015 ◽  
Vol 12 (4) ◽  
pp. 361-365 ◽  
Author(s):  
Frank DiMaio ◽  
Yifan Song ◽  
Xueming Li ◽  
Matthias J Brunner ◽  
Chunfu Xu ◽  
...  

2015 ◽  
Author(s):  
Michael A. Cianfrocco ◽  
Andres E. Leschziner

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.


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