NHC_MDynamics: High-Throughput Tools for Simulations of Complex Fluids Using Nosé-Hoover Chains and Big Data Analytics-Reference-Cited by-同舟云学术

NHC_MDynamics: High-Throughput Tools for Simulations of Complex Fluids Using Nosé-Hoover Chains and Big Data Analytics

Published:2021 Issue: Volume: Page:405-434
ISSN:1860-949X
Container-title:Studies in Computational Intelligence
language:
Short-container-title:

Author:

Guarneros-Nolasco Luis Rolando^ORCID,Suárez-Gutiérrez Manuel^ORCID,Mulia-Rodríguez Jorge^ORCID,López-Rendón Roberto^ORCID,Villanueva-Mejía Francisco^ORCID,Sánchez-Cervantes José Luis^ORCID

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-71115-3_18

Reference28 articles.

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3. Case DA, Belfon K, Ben-Shalom IY, Brozell SR, Cerutti DS, Cheatham TE III, Cruzeiro VWD et al (2020) AMBER 2020, University of California, San Francisco

4. Chebotko A, Kashlev A, Lu S (2015) A big data modeling methodology for Apache Cassandra. In: Proceedings—2015 IEEE international congress on big data, big data congress 2015. Institute of Electrical and Electronics Engineers Inc., pp 238–245

5. Doerr S, Harvey MJ, Noé F, De Fabritiis G (2016) HTMD: high-throughput molecular dynamics for molecular discovery. J Chem Theory Comput 12:1845–1852. https://doi.org/10.1021/acs.jctc.6b00049

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