Unsupervised machine learning for detection of phase transitions in off-lattice systems. II. Applications-Reference-Cited by-同舟云学术

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Unsupervised machine learning for detection of phase transitions in off-lattice systems. II. Applications

Published:2018-11-21 Issue:19 Volume:149 Page:194110
ISSN:0021-9606
Container-title:The Journal of Chemical Physics
language:en
Short-container-title:J. Chem. Phys.

Author:

Jadrich R. B.¹,Lindquist B. A.¹,Piñeros W. D.²,Banerjee D.¹,Truskett T. M.¹³^ORCID

Affiliation:

1. McKetta Department of Chemical Engineering, University of Texas at Austin, Austin, Texas 78712, USA

2. Department of Chemistry, University of Texas at Austin, Austin, Texas 78712, USA

3. Department of Physics, University of Texas at Austin, Austin, Texas 78712, USA

Funder

National Science Foundation

Welch Foundation

Publisher

AIP Publishing

Subject

Physical and Theoretical Chemistry,General Physics and Astronomy

Link

http://aip.scitation.org/doi/pdf/10.1063/1.5049850

Reference50 articles.

1. Similarities between principal components of protein dynamics and random diffusion

2. Contact- and distance-based principal component analysis of protein dynamics

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