AIMC Topic: Chemical Phenomena

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Harnessing the Power of Machine Learning Guided Discovery of NLRP3 Inhibitors Towards the Effective Treatment of Rheumatoid Arthritis.

Cells Dec 30, 2024
The NLRP3 inflammasome, plays a critical role in the pathogenesis of rheumatoid arthritis (RA) by activating inflammatory cytokines such as IL1β and IL18. Targeting NLRP3 has emerged as a promising therapeutic strategy for RA. In this study, a multid...
Machine Learning Arthritis, Rheumatoid NLR Family, Pyrin Domain-Containing 3 Protein Molecular Dynamics Simulation Chemical Phenomena Antirheumatic Agents Databases, Chemical Quantitative Structure-Activity Relationship
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MPCD: A Multitask Graph Transformer for Molecular Property Prediction by Integrating Common and Domain Knowledge.

Journal of medicinal chemistry Dec 2, 2024
Molecular property prediction with deep learning often employs self-supervised learning techniques to learn common knowledge through masked atom prediction. However, the common knowledge gained by masked atom prediction dramatically differs from the ...
Deep Learning Molecular Structure Chemical Phenomena
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From NMR to AI: Designing a Novel Chemical Representation to Enhance Machine Learning Predictions of Physicochemical Properties.

Journal of chemical information and modeling Mar 26, 2024
A novel approach to the utilization of nuclear magnetic resonance (NMR) spectroscopy data in the prediction of logD through machine learning algorithms is shown. In the analysis, a data set of 754 chemical compounds, organized into 30 clusters, was e...
Artificial Intelligence Machine Learning Algorithms Support Vector Machine Chemical Phenomena Magnetic Resonance Spectroscopy
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Chemprop: A Machine Learning Package for Chemical Property Prediction.

Journal of chemical information and modeling Dec 26, 2023
Deep learning has become a powerful and frequently employed tool for the prediction of molecular properties, thus creating a need for open-source and versatile software solutions that can be operated by nonexperts. Among the current approaches, direc...
Neural Networks, Computer Machine Learning Software Water Chemical Phenomena
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Mechanochemical Degradation of Biopolymers.

Molecules (Basel, Switzerland) Dec 10, 2023
Mechanochemical treatment of various organic molecules is an emerging technology of green processes in biofuel, fine chemicals, or food production. Many biopolymers are involved in isolating, derivating, or modifying molecules of natural origin. Mech...
Artificial Intelligence Chemical Phenomena Stress, Mechanical Biopolymers
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Recent Studies of Artificial Intelligence on Drug Absorption.

Journal of chemical information and modeling Oct 11, 2023
Absorption is an important area of research in pharmacochemistry and drug development, because the drug has to be absorbed before any drug effects can occur. Furthermore, the ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) profi...
Artificial Intelligence Databases, Factual Drug Discovery Chemical Phenomena
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MetaSpot: A General Approach for Recognizing the Reactive Atoms Undergoing Metabolic Reactions Based on the MetaQSAR Database.

International journal of molecular sciences Jul 4, 2023
The prediction of drug metabolism is attracting great interest for the possibility of discarding molecules with unfavorable ADME/Tox profile at the early stage of the drug discovery process. In this context, artificial intelligence methods can genera...
Artificial Intelligence Databases, Factual Chemical Phenomena Biotransformation
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Prediction of hydrophilic and hydrophobic hydration structure of protein by neural network optimized using experimental data.

Scientific reports Feb 7, 2023
The hydration structures of proteins, which are necessary for their folding, stability, and functions, were visualized using X-ray and neutron crystallography and transmission electron microscopy. However, complete visualization of hydration structur...
Neural Networks, Computer Water Membrane Proteins Chemical Phenomena Crystallography, X-Ray
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Statistical evaluation of testing conditions on the saturated hydraulic conductivity of Brazilian lateritic soils using artificial intelligence approaches.

Scientific reports Nov 27, 2022
The saturated hydraulic conductivity, k, is a crucial variable to describe the hydromechanical behavior of soils. The value of k of lateritic soils that are typically found in tropical regions is highly affected by the soil's structure, void ratio, a...
Artificial Intelligence Soil Brazil Chemical Phenomena Electric Conductivity
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Intelligent Fault Diagnosis for Chemical Processes Using Deep Learning Multimodel Fusion.

IEEE transactions on cybernetics Jul 4, 2022
Deep learning technology has been widely used in fault diagnosis for chemical processes. However, most deep learning technologies currently adopted only use a single network stack or a certain network stack with multilayer perceptron (MLP) behind it....
Neural Networks, Computer Deep Learning Chemical Phenomena
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