Scalable HPC & AI infrastructure for COVID-19 therapeutics

Author:

Lee Hyungro1,Merzky Andre1,Tan Li2,Titov Mikhail1,Turilli Matteo1,Alfe Dario3,Bhati Agastya3,Brace Alex4,Clyde Austin5,Coveney Peter3,Ma Heng4,Ramanathan Arvind4,Stevens Rick5,Trifan Anda6,Van Dam Hubertus2,Wan Shunzhou3,Wilkinson Sean7,Jha Shantenu1

Affiliation:

1. Rutgers University

2. Brookhaven National Laboratory

3. University College London, London, United Kingdom

4. Argonne National Laboratory

5. University of Chicago

6. University of Illinois at Urbana-Champaign

7. Oak Ridge National Laboratory

Funder

UK MRC Medical Bioinformatics project

United States Department of Energy

CANDLE project by the ECP

UCL Provost

DOE Office of Science through National Virtual Biotechnology Laboratory

UKCOMES

EU H2020 CompBioMed2 Centre of Excellence

Publisher

ACM

Reference37 articles.

1. The art and practice of structure-based drug design: A molecular modeling perspective

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3. Anthropogenic biases in chemical reaction data hinder exploratory inorganic synthesis

4. Middleware Building Blocks for Workflow Systems

5. High-Throughput Virtual Laboratory for Drug Discovery Using Massive Datasets;Glaser Jens;International Journal of High-Performance Computing Applications (to appear) (,2020

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2. Artificial intelligence and machine learning responses to COVID-19 related inquiries;Journal of Medical Engineering & Technology;2023-08-18

3. Efficient and Reliable Data Management for Biomedical Applications;Methods in Molecular Biology;2023-07-03

4. Towards a Standard Process Management Infrastructure for Workflows Using Python;Parallel and Distributed Computing, Applications and Technologies;2023

5. The Ghost of Performance Reproducibility Past;2022 IEEE 18th International Conference on e-Science (e-Science);2022-10

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