scholarly journals Assessing the transferability of common top-down and bottom-up coarse-grained molecular models for molecular mixtures

2019 ◽  
Vol 21 (4) ◽  
pp. 1912-1927 ◽  
Author(s):  
Thomas D. Potter ◽  
Jos Tasche ◽  
Mark R. Wilson
Keyword(s):  
Coarse Graining ◽  
Coarse Grained ◽  
Molecular Models ◽  
Top Down ◽  
Bottom Up ◽  
Molecular Mixtures

Assessing the performance of top-down and bottom-up coarse-graining approaches.

scholarly journals Learning neural network potentials from experimental data via Differentiable Trajectory Reweighting

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Stephan Thaler ◽  
Julija Zavadlav
Keyword(s):  
Neural Network ◽  
Experimental Data ◽  
Coarse Graining ◽  
Md Simulations ◽  
Coarse Grained ◽  
Thermodynamic Perturbation Theory ◽  
Top Down ◽  
Bottom Up ◽  
Coarse Grained Model ◽  
Gradient Computation

AbstractIn molecular dynamics (MD), neural network (NN) potentials trained bottom-up on quantum mechanical data have seen tremendous success recently. Top-down approaches that learn NN potentials directly from experimental data have received less attention, typically facing numerical and computational challenges when backpropagating through MD simulations. We present the Differentiable Trajectory Reweighting (DiffTRe) method, which bypasses differentiation through the MD simulation for time-independent observables. Leveraging thermodynamic perturbation theory, we avoid exploding gradients and achieve around 2 orders of magnitude speed-up in gradient computation for top-down learning. We show effectiveness of DiffTRe in learning NN potentials for an atomistic model of diamond and a coarse-grained model of water based on diverse experimental observables including thermodynamic, structural and mechanical properties. Importantly, DiffTRe also generalizes bottom-up structural coarse-graining methods such as iterative Boltzmann inversion to arbitrary potentials. The presented method constitutes an important milestone towards enriching NN potentials with experimental data, particularly when accurate bottom-up data is unavailable.

scholarly journals The Bipolar Logic of Feedforward and Feedback Circuits

2021 ◽  
Author(s):  
Arturo Tozzi
Keyword(s):  
Visual Recognition ◽  
Coarse Grained ◽  
William Of Ockham ◽  
Top Down ◽  
Object Persistence ◽  
Bottom Up ◽  
Bipolar Mode ◽  
External Sources ◽  
Drug Resistant Epilepsy ◽  
Work Up

Instead of the conventional 0 and 1 values, bipolar reasoning uses -1, 0, +1 to describe double-sided judgements in which neutral elements are halfway between positive and negative evaluations (e.g., “uncertain” lies between “impossible” and “totally sure”). We discuss the state-of-the-art in bipolar logics and recall two medieval forerunners, i.e., William of Ockham and Nicholas of Autrecourt, who embodied a bipolar mode of thought that is eminently modern. Starting from the trivial observation that “once a wheat sheaf is sealed and tied up, the packed down straws display the same orientation”, we work up a new theory of the bipolar nature of networks, suggesting that orthodromic (i.e., feedforward, bottom-up) projections might be functionally coupled with antidromic (i.e., feedback, top-down) projections via the mathematical apparatus of presheaves/globular sets. When an entrained oscillation such as a neuronal spike propagates from A to B, changes in B might lead to changes in A, providing unexpected antidromic effects. Our account points towards the methodological feasibility of novel neural networks in which message feedback is guaranteed by backpropagation mechanisms endowed in the same feedforward circuits. Bottom-up/top-down transmission at various coarse-grained network levels provides fresh insights in far-flung scientific fields such as object persistence, memory reinforcement, visual recognition, Bayesian inferential circuits and multidimensional activity of the brain. Implying that axonal stimulation by external sources might backpropagate and modify neuronal electric oscillations, our theory also suggests testable previsions concerning the optimal location of transcranial magnetic stimulation’s coils in patients affected by drug-resistant epilepsy.

Implicit-solvent coarse-grained modeling for polymer solutions via Mori-Zwanzig formalism

Soft Matter ◽  
2019 ◽  
Vol 15 (38) ◽  
pp. 7567-7582 ◽  
Author(s):  
Shu Wang ◽  
Zhen Li ◽  
Wenxiao Pan
Keyword(s):  
Polymer Solutions ◽  
Dynamic Properties ◽  
Coarse Graining ◽  
Coarse Grained ◽  
Implicit Solvent ◽  
Bottom Up ◽  
System P

We present a bottom-up coarse-graining (CG) method to establish implicit-solvent CG modeling for polymers in solution, which conserves the dynamic properties of the reference microscopic system.

scholarly journals The multiscale coarse-graining method. II. Numerical implementation for coarse-grained molecular models

2008 ◽  
Vol 128 (24) ◽  
pp. 244115 ◽  
Author(s):  
W. G. Noid ◽  
Pu Liu ◽  
Yanting Wang ◽  
Jhih-Wei Chu ◽  
Gary S. Ayton ◽  
...  
Keyword(s):  
Coarse Graining ◽  
Coarse Grained ◽  
Numerical Implementation ◽  
Molecular Models

scholarly journals Bottom-Up Coarse-Grained Modeling of DNA

2021 ◽  
Vol 8 ◽  
Author(s):  
Tiedong Sun ◽  
Vishal Minhas ◽  
Nikolay Korolev ◽  
Alexander Mirzoev ◽  
Alexander P. Lyubartsev ◽  
...  
Keyword(s):  
Degrees Of Freedom ◽  
Deoxyribonucleic Acid ◽  
Persistence Length ◽  
Coarse Graining ◽  
Potential Of Mean Force ◽  
Coarse Grained ◽  
Bottom Up ◽  
Slow Dynamic ◽  
Molecular Systems ◽  
Fine Grained

Recent advances in methodology enable effective coarse-grained modeling of deoxyribonucleic acid (DNA) based on underlying atomistic force field simulations. The so-called bottom-up coarse-graining practice separates fast and slow dynamic processes in molecular systems by averaging out fast degrees of freedom represented by the underlying fine-grained model. The resulting effective potential of interaction includes the contribution from fast degrees of freedom effectively in the form of potential of mean force. The pair-wise additive potential is usually adopted to construct the coarse-grained Hamiltonian for its efficiency in a computer simulation. In this review, we present a few well-developed bottom-up coarse-graining methods, discussing their application in modeling DNA properties such as DNA flexibility (persistence length), conformation, “melting,” and DNA condensation.

scholarly journals Self-assembly and mesophase formation in a non-ionic chromonic liquid crystal: insights from bottom-up and top-down coarse-grained simulation models

Soft Matter ◽  
2020 ◽  
Vol 16 (41) ◽  
pp. 9488-9498
Author(s):  
Thomas D. Potter ◽  
Martin Walker ◽  
Mark R. Wilson
Keyword(s):  
Aqueous Solution ◽  
Liquid Crystal ◽  
Self Assembly ◽  
Simulation Models ◽  
Coarse Grained ◽  
Top Down ◽  
Bottom Up ◽  
Mesophase Formation

New coarse-grained models are introduced for a non-ionic chromonic molecule, TP6EO2M, in aqueous solution.

Psychology and Culture: Top Down Versus Bottom Up?

PsycCRITIQUES ◽  
2005 ◽  
Vol 50 (19) ◽  
Author(s):  
Michael Cole
Keyword(s):  
Top Down ◽  
Bottom Up
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