AIMC Topic: Quantum Theory

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High-Accuracy Identification and Structure-Activity Analysis of Antioxidant Peptides via Deep Learning and Quantum Chemistry.

Journal of chemical information and modeling
Antioxidant peptides (AOPs) hold great promise for mitigating oxidative-stress-related diseases, but their discovery is hindered by inefficient and time-consuming traditional methods. To address this, we developed an innovative framework combining ma...

Evaluation of Machine Learning/Molecular Mechanics End-State Corrections with Mechanical Embedding to Calculate Relative Protein-Ligand Binding Free Energies.

Journal of chemical theory and computation
The development of machine-learning (ML) potentials offers significant accuracy improvements compared to molecular mechanics (MM) because of the inclusion of quantum-mechanical effects in molecular interactions. However, ML simulations are several ti...

Quantum-resilient software security: A fuzzy AHP-based assessment framework in the era of quantum computing.

PloS one
The introduction of quantum computing has transformed the setting of information technology, bringing both unprecedented opportunities and significant challenges. As quantum technologies continue to evolve, addressing their implications for software ...

Synergizing quantum techniques with machine learning for advancing drug discovery challenge.

Scientific reports
The Quantum Computing for Drug Discovery Challenge, held at the 42nd International Conference on Computer-Aided Design (ICCAD) in 2023, was a multi-month, research-intensive competition. Over 70 teams from more than 65 organizations from 12 different...

Deep Learning Prediction of Drug-Induced Liver Toxicity by Manifold Embedding of Quantum Information of Drug Molecules.

Pharmaceutical research
PURPOSE: Drug-induced liver injury, or DILI, affects numerous patients and also presents significant challenges in drug development. It has been attempted to predict DILI of a chemical by in silico approaches, including data-driven machine learning m...

Self-supervised pre-trained neural network for quantum natural language processing.

Neural networks : the official journal of the International Neural Network Society
Quantum computing models have propelled advances in many application domains. However, in the field of natural language processing (NLP), quantum computing models are limited in representation capacity due to the high linearity of the underlying quan...

Rehabilitation Technologies by Integrating Exoskeletons, Aquatic Therapy, and Quantum Computing for Enhanced Patient Outcomes.

Sensors (Basel, Switzerland)
Recent advancements in patient rehabilitation integrate both traditional and modern techniques to enhance treatment efficacy and accessibility. Hydrotherapy, leveraging water's physical properties, is crucial for reducing joint stress, alleviating pa...

Quantum-inspired neural network with hierarchical entanglement embedding for matching.

Neural networks : the official journal of the International Neural Network Society
Quantum-inspired neural networks (QNNs) have shown potential in capturing various non-classical phenomena in language understanding, e.g., the emgerent meaning of concept combinations, and represent a leap beyond conventional models in cognitive scie...

Quantum Computing in Medicine.

Medical sciences (Basel, Switzerland)
Quantum computing (QC) represents a paradigm shift in computational power, offering unique capabilities for addressing complex problems that are infeasible for classical computers. This review paper provides a detailed account of the current state of...

Ab initio characterization of protein molecular dynamics with AIBMD.

Nature
Biomolecular dynamics simulation is a fundamental technology for life sciences research, and its usefulness depends on its accuracy and efficiency. Classical molecular dynamics simulation is fast but lacks chemical accuracy. Quantum chemistry methods...