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Exscalate4CoV - High-Performance Computing for Covid Drug Discovery (1st ed. 2023) Loot Price: R1,479
Discovery Miles 14 790
Exscalate4CoV - High-Performance Computing for Covid Drug Discovery (1st ed. 2023): Silvano Coletti, Gabriella Bernardi

Exscalate4CoV - High-Performance Computing for Covid Drug Discovery (1st ed. 2023)

Silvano Coletti, Gabriella Bernardi

Series: SpringerBriefs in Applied Sciences and Technology

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Loot Price R1,479 Discovery Miles 14 790 | Repayment Terms: R139 pm x 12*

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This book highlights the different aspects of the research project “E4C Horizon 2020 European Project” aimed at fighting the coronavirus by combining the best supercomputing resources and artificial intelligence with state-of-the-art experimental facilities up through clinical validation. Coronavirus disease has become an important public issue across the globe since December 2019. There is an urgent need to develop potent anti-COVID-19 agents for the prevention of the outbreak and stop viral infections. To this aim, a public–private consortium composed by European and national infrastructures, center of excellence, universities, and a pharmaceutical company started the E4C Horizon 2020 European Project: Its core idea was to use the EXaSCale smArt pLatform Against paThogEns (EXSCALATE) supercomputing platform for a process known as “drug repurposing”, namely to identify the most promising safe in man drugs for immediate treatment of the already infected population and then novel pan-coronavirus inhibitors to address future emergencies. This ambitious goal exploited a “chemical library” of 500 billion molecules, thanks to a processing capacity of more than 3 million molecules per second, made available by the computing power of the EXSCALATE platform.

General

Imprint: Springer International Publishing AG
Country of origin: Switzerland
Series: SpringerBriefs in Applied Sciences and Technology
Release date: May 2023
Firstpublished: 2023
Editors: Silvano Coletti • Gabriella Bernardi
Dimensions: 235 x 155mm (L x W)
Edition: 1st ed. 2023
ISBN-13: 978-3-03-130690-7
Categories: Books
LSN: 3-03-130690-2
Barcode: 9783031306907

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