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Topological obstructions in the way of data-driven collective variables

Autor
Hashemian, B.; Arroyo, M.
Tipus d'activitat
Article en revista
Revista
Journal of chemical physics
Data de publicació
2015-01-28
Volum
142
Número
4
Pàgina inicial
044102-1
Pàgina final
044102-6
DOI
https://doi.org/10.1063/1.4906425 Obrir en finestra nova
Repositori
http://hdl.handle.net/2117/27154 Obrir en finestra nova
URL
http://scitation.aip.org/content/aip/journal/jcp/142/4/10.1063/1.4906425 Obrir en finestra nova
Resum
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...
Citació
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.
Paraules clau
DIFFUSION MAPS, FREE-ENERGY LANDSCAPES, MANIFOLDS, MOLECULAR-DYNAMICS SIMULATIONS, NONLINEAR DIMENSIONALITY REDUCTION, PROTEINS, SKETCH-MAP, SPACE
Grup de recerca
LACÀN - Mètodes Numèrics en Ciències Aplicades i Enginyeria

Participants

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