Accelerated Simulations of Molecular Systems through Learning of Effective Dynamics-Reference-Cited by-同舟云学术

Accelerated Simulations of Molecular Systems through Learning of Effective Dynamics

Published:2021-12-10 Issue:1 Volume:18 Page:538-549
ISSN:1549-9618
Container-title:Journal of Chemical Theory and Computation
language:en
Short-container-title:J. Chem. Theory Comput.

Author:

Vlachas Pantelis R.¹,Zavadlav Julija²³^ORCID,Praprotnik Matej⁴⁵^ORCID,Koumoutsakos Petros⁶^ORCID

Affiliation:

1. Computational Science and Engineering Laboratory, ETH Zurich, CH-8092, Switzerland

2. Professorship of Multiscale Modeling of Fluid Materials, TUM School of Engineering and Design, Technical University of Munich, 85748 Garching bei München, Germany

3. Munich Data Science Institute, Technical University of Munich, 85748 Munich, Germany

4. Laboratory for Molecular Modeling, National Institute of Chemistry, SI-1001 Ljubljana, Slovenia

5. Department of Physics, Faculty of Mathematics and Physics, University of Ljubljana, SI-1000 Ljubljana, Slovenia

6. John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts 02138, United States

Funder

Javna Agencija za Raziskovalno Dejavnost RS

Publisher

American Chemical Society (ACS)

Subject

Physical and Theoretical Chemistry,Computer Science Applications

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jctc.1c00809

Reference88 articles.

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4. Principal Component Analysis and Long Time Protein Dynamics

5. Harmonic dynamics of proteins: normal modes and fluctuations in bovine pancreatic trypsin inhibitor.

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