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An ultra-high-performance protein-protein docking for heterogeneous supercomputers

Home Page: http://www.bi.cs.titech.ac.jp/megadock/

License: Other

C++ 96.74% Python 0.10% Perl 0.08% Cuda 1.96% Makefile 0.97% Dockerfile 0.14%

megadock's Introduction

MEGADOCK

MEGADOCK is an ultra-high-performance protein-protein prediction software for heterogeneous supercomputers using FFT-grid-based docking with MPI/OpenMP/GPU parallelization.

License: CC BY-NC 4.0 License: CC BY-NC 4.0

Build Status

Target Environments

Type Target Env. Approach
(a) GPU cluster GPU + OpenMP + MPI
(b) CPU cluster OpenMP + MPI
(c) GPU node GPU + OpenMP
(d) CPU node OpenMP

Installation and Command Details

For installation and command details, please read appropriate section on followings:

Reference

Masahito Ohue, Takehiro Shimoda, Shuji Suzuki, Yuri Matsuzaki, Takashi Ishida, Yutaka Akiyama. MEGADOCK 4.0: an ultra-high-performance protein-protein docking software for heterogeneous supercomputers, Bioinformatics, 30(22): 3281-3283, 2014. http://doi.org/10.1093/bioinformatics/btu532

Masahito Ohue, Yuri Matsuzaki, Nobuyuki Uchikoga, Takashi Ishida, Yutaka Akiyama. MEGADOCK: An all-to-all protein-protein interaction prediction system using tertiary structure data, Protein and Peptide Letters, 21(8): 766-778, 2014. https://doi.org/10.2174/09298665113209990050

Older Versions

http://www.bi.cs.titech.ac.jp/megadock/archives/

License

MEGADOCK is licensed by CC BY-NC 4.0. (See LICENSE) This software and derivatives are NOT allowed for any commercial use without formal prior authorization by Tokyo Institute of Technology. Please contact us about commercial use. If you are considering commercial use, please contact us as there are different charged use options licensed by the Tokyo Institute of Technology.

Fundings

This work is partially supported by JSPS Grant-in-Aid for Scientific Research (KAKENHI) (A) Grant Number 24240044.


Copyright © 2014-2022 Akiyama Laboratory, Tokyo Institute of Technology, All Rights Reserved.

megadock's People

Contributors

metavariable avatar tonets avatar hi-watana avatar akiyamalab-web avatar

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