Results 151 to 160 of about 36,435 (290)

Study on Phosphorus Compound/Catechol‐Catalyzed Dehydrative Amidation and Its Database Development for Machine Learning

open access: yesChemistry – A European Journal, EarlyView.
A novel phosphorus‐based catalytic system for the direct amidation of carboxylic acids with amines has been developed. The efficiency of the phosphorus catalysis is substantially enhanced using catechol derivatives as additives. A vault of experimental data obtained this time was complemented with ML models, which allowed capturing the intricate ...
Taiki Nagano   +6 more
wiley   +1 more source

The Face of Emotion: Botulinum Toxin, Emotional Anatomy, and Mood Modulation. [PDF]

open access: yesJ Cosmet Dermatol
Vanaria RJ   +4 more
europepmc   +1 more source

MLPROP – An Interactive Web Interface for Thermophysical Property Prediction with Machine Learning

open access: yesChemie Ingenieur Technik, EarlyView.
MLPROP is an open‐access, web‐based interface for predicting thermophysical properties of pure substances and mixtures by machine learning models. Integrating GRAPPA, UNIFAC 2.0, mod. UNIFAC 2.0, and HANNA, it enables accurate and accessible predictions of vapor pressures, activity coefficients, and vapor‐liquid equilibria without requiring users to ...
Marco Hoffmann   +4 more
wiley   +1 more source

Beyond Docking: A Multitier Computational Pipeline for USP7 Inhibitor Optimization

open access: yesChemMedChem, EarlyView.
A multitier computational strategy discovers potential USP7 inhibitors using similarity‐based virtual screening, physics‐driven molecular simulations, binding free energy estimations, binary QSAR modeling, and steered molecular dynamics analysis. This integrated approach prioritizes and optimizes lead compounds with strong predicted affinity, offering ...
Ehsan Sayyah   +2 more
wiley   +1 more source

Brain Plasticity and the Labbé Procedure: Where do we stand? [PDF]

open access: yesJPRAS Open
Yu Wong Z   +5 more
europepmc   +1 more source

An Efficient Method Using Small‐Sized Datasets Based upon Generative Adversarial Networks: Investigation of Cluster Configuration Space

open access: yesChemistry–Methods, EarlyView.
An efficient method based on generative adversarial networks is proposed using small‐sized datasets. The atomic and molecular cluster configuration spaces are investigated to show the generation ability of the proposed method. Benchmark results demonstrate superior performance over the widely used genetic algorithms.
Jintao Xie, Qing Lu, Wensheng Bian
wiley   +1 more source

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