AIMC Topic: Quantum Theory

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Machine Learning Classification of Chirality and Optical Rotation Using a Simple One-Hot Encoded Cartesian Coordinate Molecular Representation.

Journal of chemical information and modeling May 12, 2025
Absolute stereochemical configurations and optical rotations were computed for 121,416 molecular structures from the QM9 quantum chemistry data set using density functional theory. A representation for the molecules was developed using Cartesian coor...
Stereoisomerism Optical Rotation Models, Molecular Machine Learning Quantum Theory Algorithms
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The Quest for Cognition in Purposive Action: From Cybernetics to Quantum Computing.

Journal of integrative neuroscience Feb 16, 2023
Norbert Wiener and Nikolai Bernstein set the stage for a worldwide multidisciplinary attempt to understand how purposive action is integrated with cognition in a circular, bidirectional manner, both in life sciences and engineering. Such a 'workshop'...
Humans Artificial Intelligence Cybernetics Computing Methodologies Cognition Quantum Theory
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A deep transfer learning-based protocol accelerates full quantum mechanics calculation of protein.

Briefings in bioinformatics Jan 19, 2023
Effective full quantum mechanics (FQM) calculation of protein remains a grand challenge and of great interest in computational biology with substantial applications in drug discovery, protein dynamic simulation and protein folding. However, the huge ...
Neural Networks, Computer Proteins Machine Learning Quantum Theory Algorithms
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Interatomic force from neural network based variational quantum Monte Carlo.

The Journal of chemical physics Oct 28, 2022
Accurate ab initio calculations are of fundamental importance in physics, chemistry, biology, and materials science, which have witnessed rapid development in the last couple of years with the help of machine learning computational techniques such as...
Materials Science Quantum Theory Neural Networks, Computer Monte Carlo Method Machine Learning
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Gell-Mann-Low Criticality in Neural Networks.

Physical review letters Apr 22, 2022
Criticality is deeply related to optimal computational capacity. The lack of a renormalized theory of critical brain dynamics, however, so far limits insights into this form of biological information processing to mean-field results. These methods ne...
Quantum Theory Normal Distribution Neural Networks, Computer Brain
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Artificial Intelligence and Quantum Computing as the Next Pharma Disruptors.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2022
Artificial intelligence (AI) consists of a synergistic assembly of enhanced optimization strategies with wide application in drug discovery and development, providing advanced tools for promoting cost-effectiveness throughout drug life cycle. Specifi...
Pharmaceutical Preparations Quantum Theory Humans Artificial Intelligence
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Mol2Context-vec: learning molecular representation from context awareness for drug discovery.

Briefings in bioinformatics Nov 5, 2021
With the rapid development of proteomics and the rapid increase of target molecules for drug action, computer-aided drug design (CADD) has become a basic task in drug discovery. One of the key challenges in CADD is molecular representation. High-qual...
Humans Algorithms Drug Design Drug Discovery Cheminformatics Models, Molecular Deep Learning Quantum Theory Structure-Activity Relationship
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Machine learning builds full-QM precision protein force fields in seconds.

Briefings in bioinformatics Nov 5, 2021
Full-quantum mechanics (QM) calculations are extraordinarily precise but difficult to apply to large systems, such as biomolecules. Motivated by the massive demand for efficient calculations for large systems at the full-QM level and by the significa...
Databases, Protein Molecular Dynamics Simulation Quantum Theory Protein Conformation Computational Biology Proteins Reproducibility of Results Peptides Neural Networks, Computer Machine Learning Algorithms
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DeepAtomicCharge: a new graph convolutional network-based architecture for accurate prediction of atomic charges.

Briefings in bioinformatics May 20, 2021
Atomic charges play a very important role in drug-target recognition. However, computation of atomic charges with high-level quantum mechanics (QM) calculations is very time-consuming. A number of machine learning (ML)-based atomic charge prediction ...
Neural Networks, Computer Molecular Structure Quantum Theory Machine Learning Drug Design
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A machine learning based intramolecular potential for a flexible organic molecule.

Faraday discussions Dec 4, 2020
Quantum mechanical predictive modelling in chemistry and biology is often hindered by the long time scales and large system sizes required of the computational model. Here, we employ the kernel regression machine learning technique to construct an an...
p38 Mitogen-Activated Protein Kinases Machine Learning Quantum Theory Software Epoxide Hydrolases Protein Binding Monte Carlo Method Organic Chemicals Thermodynamics
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