HPC Module: AlphaFold
Synopsis
AlphaFold can accurately predict 3D models of protein structures and has the potential to accelerate research in every field of biology.
| About This Software | |
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| Official Site | https://github.com/deepmind/alphafold |
| Tags |
Installed Versions
| Version | Install Date | Default? |
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| 2.0 | 2021-08-04 |
Description
This package provides an implementation of the inference pipeline of AlphaFold v2.0. This is a completely new model that was entered in CASP14 and published in Nature. For simplicity, we refer to this model as AlphaFold throughout the rest of this document.
This module depends on a singularity image. To make usage easier, an alias has been created named raf.sh which handles most of the options that are unlikely to change from run to run.
Citation(s)
If you use AlphaFold in your research, please cite: If you use the code or data in this package, please cite:
@Article{AlphaFold2021,
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author = {Jumper, John and Evans, Richard and Pritzel, Alexander and Green, Tim and Figurnov, Michael and Ronneberger, Olaf and Tunyasuvunakool, Kathryn and Bates, Russ and {v{Z}}{'i}dek, Augustin and Potapenko, Anna and Bridgland, Alex and Meyer, Clemens and Kohl, Simon A A and Ballard, Andrew J and Cowie, Andrew and Romera-Paredes, Bernardino and Nikolov, Stanislav and Jain, Rishub and Adler, Jonas and Back, Trevor and Petersen, Stig and Reiman, David and Clancy, Ellen and Zielinski, Michal and Steinegger, Martin and Pacholska, Michalina and Berghammer, Tamas and Bodenstein, Sebastian and Silver, David and Vinyals, Oriol and Senior, Andrew W and Kavukcuoglu, Koray and Kohli, Pushmeet and Hassabis, Demis},
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journal = {Nature},
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title = {Highly accurate protein structure prediction with {AlphaFold}},
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year = {2021},
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doi = {10.1038/s41586-021-03819-2},
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note = {(Accelerated article preview)}, }
Category
| Library | Programming | Software | SysAdmin |
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