AIMC Journal:
Molecules (Basel, Switzerland)

Showing 161 to 170 of 243 articles

Prediction of Premature Termination Codon Suppressing Compounds for Treatment of Duchenne Muscular Dystrophy Using Machine Learning.

Molecules (Basel, Switzerland) Aug 26, 2020
A significant percentage of Duchenne muscular dystrophy (DMD) cases are caused by premature termination codon (PTC) mutations in the dystrophin gene, leading to the production of a truncated, non-functional dystrophin polypeptide. PTC-suppressing com...
Databases, Chemical Muscular Dystrophy, Duchenne Codon, Terminator Humans Machine Learning Dystrophin
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The Fuzziness in Molecular, Supramolecular, and Systems Chemistry.

Molecules (Basel, Switzerland) Aug 10, 2020
The global challenges of the XXI century require a more in-depth analysis and investigation of complex systems [...].
Fuzzy Logic Models, Chemical Kinetics Artificial Intelligence
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A Novel Hybrid Model Based on a Feedforward Neural Network and One Step Secant Algorithm for Prediction of Load-Bearing Capacity of Rectangular Concrete-Filled Steel Tube Columns.

Molecules (Basel, Switzerland) Jul 31, 2020
In this study, a novel hybrid surrogate machine learning model based on a feedforward neural network (FNN) and one step secant algorithm (OSS) was developed to predict the load-bearing capacity of concrete-filled steel tube columns (CFST), whereas th...
Databases, Factual Models, Theoretical Construction Industry Weight-Bearing Engineering Neural Networks, Computer Construction Materials Steel Machine Learning
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Moonlighting Proteins in the Fuzzy Logic of Cellular Metabolism.

Molecules (Basel, Switzerland) Jul 29, 2020
The numerous interconnected biochemical pathways that make up the metabolism of a living cell comprise a fuzzy logic system because of its high level of complexity and our inability to fully understand, predict, and model the many activities, how the...
Fuzzy Logic Proteins Models, Biological Energy Metabolism Metabolic Networks and Pathways Humans Animals Protein Binding
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Artificial Intelligence Methods for Constructing Wine Barrels with a Controlled Oxygen Transmission Rate.

Molecules (Basel, Switzerland) Jul 21, 2020
Oxygen is an important factor in the wine aging process, and the oxygen transmission rate (OTR) is the parameter of the wood that reflects its oxygen permeation. OTR has not been considered in the cooperage industry yet; however, recent studies propo...
Artificial Intelligence Oxidation-Reduction Oxygen Wine Time Factors Food Packaging Wood
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Modeling of Cu(II) Adsorption from an Aqueous Solution Using an Artificial Neural Network (ANN).

Molecules (Basel, Switzerland) Jul 17, 2020
This research optimized the adsorption performance of rice husk char (RHC4) for copper (Cu(II)) from an aqueous solution. Various physicochemical analyses such as Fourier transform infrared spectroscopy (FTIR), field-emission scanning electron micros...
Thermodynamics Sulfur Solutions Adsorption Models, Molecular Kinetics Diffusion Copper Water Water Pollutants, Chemical Neural Networks, Computer Algorithms
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SUSSOL-Using Artificial Intelligence for Greener Solvent Selection and Substitution.

Molecules (Basel, Switzerland) Jul 3, 2020
Solvents come in many shapes and types. Looking for solvents for a specific application can be hard, and looking for green alternatives for currently used nonbenign solvents can be even harder. We describe a new methodology for solvent selection and ...
Software Algorithms Neural Networks, Computer Solvents Green Chemistry Technology Artificial Intelligence Humans Databases, Factual
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The Study on the hERG Blocker Prediction Using Chemical Fingerprint Analysis.

Molecules (Basel, Switzerland) Jun 4, 2020
Human ether-a-go-go-related gene (hERG) potassium channel blockage by small molecules may cause severe cardiac side effects. Thus, it is crucial to screen compounds for activity on the hERG channels early in the drug discovery process. In this study,...
Humans Drug Discovery Algorithms Machine Learning Models, Molecular Computer Simulation Ether-A-Go-Go Potassium Channels Quantitative Structure-Activity Relationship Potassium Channel Blockers
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Magnetic Elements for Neuromorphic Computing.

Molecules (Basel, Switzerland) May 30, 2020
Neuromorphic computing is assumed to be significantly more energy efficient than, and at the same time expected to outperform, conventional computers in several applications, such as data classification, since it overcomes the so-called von Neumann b...
Cognition Nanostructures Humans Software Neural Networks, Computer Animals
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A Deep-Learning Approach toward Rational Molecular Docking Protocol Selection.

Molecules (Basel, Switzerland) May 27, 2020
While a plethora of different protein-ligand docking protocols have been developed over the past twenty years, their performances greatly depend on the provided input protein-ligand pair. In this study, we developed a machine-learning model that uses...
Databases, Protein Cheminformatics Molecular Docking Simulation Machine Learning Deep Learning
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