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Topological obstructions in the way of data-driven collective variables

Author
Hashemian, B.; Arroyo, M.
Type of activity
Journal article
Journal
Journal of chemical physics
Date of publication
2015-01-28
Volume
142
Number
4
First page
044102-1
Last page
044102-6
DOI
https://doi.org/10.1063/1.4906425 Open in new window
Repository
http://hdl.handle.net/2117/27154 Open in new window
URL
http://scitation.aip.org/content/aip/journal/jcp/142/4/10.1063/1.4906425 Open in new window
Abstract
Nonlinear dimensionality reduction (NLDR) techniques are increasingly used to visualize molecular trajectories and to create data-driven collective variables for enhanced sampling simulations. The success of these methods relies on their ability to identify the essential degrees of freedom characterizing conformational changes. Here, we show that NLDR methods face serious obstacles when the underlying collective variables present periodicities, e.g., arising from proper dihedral angles. As a res...
Citation
Hashemian, B.; Arroyo, M. Topological obstructions in the way of data-driven collective variables. "Journal of chemical physics", 28 Gener 2015, vol. 142, núm. 4, p. 044102-1-044102-6.
Keywords
DIFFUSION MAPS, FREE-ENERGY LANDSCAPES, MANIFOLDS, MOLECULAR-DYNAMICS SIMULATIONS, NONLINEAR DIMENSIONALITY REDUCTION, PROTEINS, SKETCH-MAP, SPACE
Group of research
LACÀN - Numerical Methods for Applied Sciences and Engineering

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