Cargando…
Coarse-Grained Modeling Using Neural Networks Trained on Structural Data
[Image: see text] We propose a method of bottom-up coarse-graining, in which interactions within a coarse-grained model are determined by an artificial neural network trained on structural data obtained from multiple atomistic simulations. The method uses ideas of the inverse Monte Carlo approach, r...
Autores principales: | Ivanov, Mikhail, Posysoev, Maksim, Lyubartsev, Alexander P. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2023
|
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10569054/ https://www.ncbi.nlm.nih.gov/pubmed/37712507 http://dx.doi.org/10.1021/acs.jctc.3c00516 |
Ejemplares similares
-
Bottom-Up Coarse-Grained Modeling of DNA
por: Sun, Tiedong, et al.
Publicado: (2021) -
Coarse-Grained
Simulation of Rodlike Higher-Order
Quadruplex Structures at Different Salt Concentrations
por: Rebič, Matúš, et al.
Publicado: (2017) -
Implicit solvent systematic coarse-graining of dioleoylphosphatidylethanolamine lipids: From the inverted hexagonal to the bilayer structure
por: Mortezazadeh, Saeed, et al.
Publicado: (2019) -
A Bottom-Up Coarse-Grained Model for Nucleosome–Nucleosome
Interactions with Explicit Ions
por: Sun, Tiedong, et al.
Publicado: (2022) -
Coarse-Grained Pruning of Neural Network Models Based on Blocky Sparse Structure
por: Huang, Lan, et al.
Publicado: (2021)