Machine Learning in Soft Matter: From Simulations to Experiments
K Zhang, X Gong, Y Jiang - Advanced Functional Materials, 2024 - Wiley Online Library
Soft matter with diverse functionalities that are easily designable has fascinated tremendous
research interests in the past several decades. Nevertheless, the inherent confluence of time …
research interests in the past several decades. Nevertheless, the inherent confluence of time …
Lipid Landscapes: Vibrational Spectroscopy for Decoding Membrane Complexity
Cell membranes are incredibly complex environments containing hundreds of components.
Despite substantial advances in the past decade, fundamental questions related to lipid-lipid …
Despite substantial advances in the past decade, fundamental questions related to lipid-lipid …
Influence of the Water Model on the Structure and Interactions of the GPR40 Protein with the Lipid Membrane and the Solvent: Rigid versus Flexible Water Models
JA Aguilar-Pineda… - Journal of Chemical …, 2024 - ACS Publications
G protein-coupled receptors (GPCR) are responsible for modulating various physiological
functions and are thus related to the pathophysiology of different diseases. Being potential …
functions and are thus related to the pathophysiology of different diseases. Being potential …
[HTML][HTML] On the structure and stability of novel cationic DPPC liposomes doped with gemini surfactants
V Domínguez-Arca, J Sabín, L García-Río… - Journal of Molecular …, 2022 - Elsevier
A novel formulation of cationic liposomes was studied by mixing
dipalmitoylphosphatidylcholine (DPPC) with tetradecyltrimethylammonium bromide gemini …
dipalmitoylphosphatidylcholine (DPPC) with tetradecyltrimethylammonium bromide gemini …
Machine learning platform for determining experimental lipid phase behaviour from small angle X-ray scattering patterns by pre-training on synthetic data
Lipid membranes are vital in a wide range of biological and biotechnical systems; they
undepin functions from modulation of protein activity to drug uptake and delivery …
undepin functions from modulation of protein activity to drug uptake and delivery …
Predicting the DNA conductance using a deep feedforward neural network model
Double-stranded DNA (dsDNA) has been established as an efficient medium for charge
migration, bringing it to the forefront of the field of molecular electronics and biological …
migration, bringing it to the forefront of the field of molecular electronics and biological …
Elucidating lipid conformations in the ripple phase: Machine learning reveals four lipid populations
A new mixed radial-angular, three-particle correlation function method in combination with
unsupervised machine learning was applied to examine the emergence of the ripple phase …
unsupervised machine learning was applied to examine the emergence of the ripple phase …
Machine learning-assisted phase transition temperatures from generalized replica exchange simulations of dry martini lipid bilayers
ZA Piskulich, Q Cui - The Journal of Physical Chemistry Letters, 2022 - ACS Publications
Accurate estimation of phase transition temperatures has been a longstanding challenge for
molecular simulations. Recently, the generalized Replica Exchange technique for estimating …
molecular simulations. Recently, the generalized Replica Exchange technique for estimating …
[HTML][HTML] Ripple-like instability in the simulated gel phase of finite size phosphocholine bilayers
Atomistic molecular dynamics simulations have reached a degree of maturity that makes it
possible to investigate the lipid polymorphism of model bilayers over a wide range of …
possible to investigate the lipid polymorphism of model bilayers over a wide range of …
Decoding Interaction Patterns from the Chemical Sequence of Polymers Using Neural Networks
M Werner - ACS Macro Letters, 2021 - ACS Publications
The relation between chemical sequences and the properties of polymers is considered
using artificial neural networks with a low-dimensional bottleneck layer of neurons. These …
using artificial neural networks with a low-dimensional bottleneck layer of neurons. These …