Connected Component Analysis of Dynamical Perturbation Contact Networks-Reference-Cited by-同舟云学术

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Connected Component Analysis of Dynamical Perturbation Contact Networks

Published:2023-08-29 Issue:35 Volume:127 Page:7571-7580
ISSN:1520-6106
Container-title:The Journal of Physical Chemistry B
language:en
Short-container-title:J. Phys. Chem. B

Author:

Gheeraert Aria¹²,Lesieur Claire³⁴^ORCID,Batista Victor S.⁵^ORCID,Vuillon Laurent¹⁴,Rivalta Ivan²⁶^ORCID

Affiliation:

1. Laboratoire de Mathématiques (LAMA), Université Savoie Mont Blanc, CNRS, 73376 Le Bourget du Lac, France

2. Dipartimento di Chimica Industriale “Toso Montanari”, Alma Mater Studiorum, Università di Bologna, Viale del Risorgimento 4, 40136 Bologna, Italy

3. Univ. Lyon, CNRS, INSA Lyon, Université Claude Bernard Lyon 1, Ecole Centrale de Lyon, Ampère UMR5005, Villeurbanne 69622, France

4. Institut Rhônalpin des Systèmes Complexes, IXXI-ENS-Lyon, Lyon 69007, France

5. Department of Chemistry, Yale University, New Haven, Connecticut 06520, United States

6. ENS de Lyon, CNRS, Laboratoire de Chimie UMR 5182, 69364 Lyon, France

Funder

Fondation de l'Ecole Normale Superieure

Centre National de la Recherche Scientifique

Federation of European Biochemical Societies

National Institute of General Medical Sciences

Institut Rhonalpin

Publisher

American Chemical Society (ACS)

Subject

Materials Chemistry,Surfaces, Coatings and Films,Physical and Theoretical Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jpcb.3c04592

Reference72 articles.

1. How Fast-Folding Proteins Fold

2. Shaw, D. E.; Grossman, J.; Bank, J. A.; Batson, B.; Butts, J. A.; Chao, J. C.; Deneroff, M. M.; Dror, R. O.; Even, A.; Fenton, C. H. Anton 2: raising the bar for performance and programmability in a special-purpose molecular dynamics supercomputer. SC’14: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis. 2014; pp 41–53.

3. Decrypting the Information Exchange Pathways across the Spliceosome Machinery

4. Scaling molecular dynamics beyond 100,000 processor cores for large‐scale biophysical simulations

5. New parallel computing algorithm of molecular dynamics for extremely huge scale biological systems

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