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Title
Japanese: 
English:MEGADOCK 3.0: A high-performance protein-protein interaction prediction software using hybrid parallel computing for petascale supercomputing environments 
Author
Japanese: 松崎 由理, 内古閑 伸之, 大上 雅史, 下田 雄大, 佐藤 智之, 石田 貴士, 秋山 泰.  
English: Yuri Matsuzaki, Nobuyuki Uchikoga, Masahito Ohue, Takehiro Shimoda, Toshiyuki Sato, Takashi Ishida, Yutaka Akiyama.  
Language English 
Journal/Book name
Japanese: 
English:Source Code for Biology and Medicine 
Volume, Number, Page Vol. 8    No. 1   
Published date Sept. 3, 2013 
Publisher
Japanese: 
English:BioMed Central 
Conference name
Japanese: 
English: 
Conference site
Japanese: 
English: 
Official URL http://www.scfbm.org/content/8/1/18/
 
DOI https://doi.org/10.1186/1751-0473-8-18
Abstract Background Protein-protein interaction (PPI) plays a core role in cellular functions. Massively parallel supercomputing systems have been actively developed over the past few years, which enable large-scale biological problems to be solved, such as PPI network prediction based on tertiary structures. Results We have developed a high throughput and ultra-fast PPI prediction system based on rigid docking, “MEGADOCK”, by employing a hybrid parallelization (MPI/OpenMP) technique assuming usages on massively parallel supercomputing systems. MEGADOCK displays significantly faster processing speed in the rigid-body docking process that leads to full utilization of protein tertiary structural data for large-scale and network-level problems in systems biology. Moreover, the system was scalable as shown by measurements carried out on two supercomputing environments. We then conducted prediction of biological PPI networks using the post-docking analysis. Conclusions We present a new protein-protein docking engine aimed at exhaustive docking of mega-order numbers of protein pairs. The system was shown to be scalable by running on thousands of nodes. The software package is available at: http://www.bi.cs.titech.ac.jp/megadock/k/.

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