AIMC Topic: Hydrophobic and Hydrophilic Interactions
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Explainability of Protein Deep Learning Models.
International journal of molecular sciences
May 29, 2025
Protein embeddings are the new main source of information about proteins, producing state-of-the-art solutions to many problems, including protein interaction prediction, a fundamental issue in proteomics. Understanding the embeddings and what causes...
Dynamics and Machine Learning Reveal the Link between Tripeptide Sequences and Evaporation-Driven Material Properties.
Nano letters
Apr 27, 2025
Previous research showed that a peptide composed of three tyrosines (YYY) can turn into organic glass and cause strong adhesion between substrates via evaporation. However, the mechanisms of these processes remain unclear, and the exploration of appl...
Surrogate modeling of electrospun PVA/PLA nanofibers using artificial neural network for biomedical applications.
Scientific reports
Apr 15, 2025
Blending poly (lactic acid) (PLA) with poly (vinyl alcohol) (PVA) improves the strength and hydrophilicity of nanofibers, making them suitable for biomedical applications like wound dressings. This study explores how electrospinning parameters-applie...
Compact Assessment of Molecular Surface Complementarities Enhances Neural Network-Aided Prediction of Key Binding Residues.
Journal of chemical information and modeling
Feb 21, 2025
Predicting interactions between proteins is fundamental for understanding the mechanisms underlying cellular processes, since protein-protein complexes are crucial in physiological conditions but also in many diseases, for example by seeding aggregat...
An intelligent fruit freshness monitoring system using hydrophobic indicator labels based on methylcellulose, k-carrageenan, and sodium tripolyphosphate, combined with deep learning.
International journal of biological macromolecules
Jan 17, 2025
As the demand for food quality and safety continues to rise, pH-responsive intelligent packaging technologies have found widespread application in the monitoring of food freshness. This study introduces a methylcellulose (MC)-based indicator label de...
Highly sensitive, breathable, and superhydrophobic dome structure nonwoven-based flexible pressure sensor utilizing machine learning for handwriting recognition.
International journal of biological macromolecules
Jan 13, 2025
Wearable devices that incorporate flexible pressure sensors have shown great potential for human-machine interaction, speech recognition, health monitoring, and handwriting recognition. However, achieving high sensitivity, durability, wide detection ...
Computational approaches for decoding structure-saltiness enhancement and aroma perception mechanisms of odorants: From machine learning to molecular simulation.
Food research international (Ottawa, Ont.)
Jan 7, 2025
The unclear relationship between structure and saltiness enhancement limits the development and application of savory odorants. The structure characteristic-saltiness enhancement perception (SEP) mechanisms of savory odorants were investigated by mac...
Antimicrobial Peptides as Broad-Spectrum Therapeutics: Computational Analysis to Identify Universal Physical-Chemical Features Responsible for Multitarget Activity.
The journal of physical chemistry letters
Dec 11, 2024
Antimicrobial peptides (AMPs) hold significant potential as broad-spectrum therapeutics due to their ability to target a variety of different pathogens, including bacteria, fungi, and viruses. However, the rational design of these peptides requires t...
Hierarchical Graph Attention Network with Positive and Negative Attentions for Improved Interpretability: ISA-PN.
Journal of chemical information and modeling
Dec 9, 2024
With the advancement of deep learning (DL) methods in chemistry and materials science, the interpretability of DL models has become a critical issue in elucidating quantitative (molecular) structure-property relationships. Although attention mechanis...
Investigating the Bromoform Membrane Interactions Using Atomistic Simulations and Machine Learning: Implications for Climate Change Mitigation.
The journal of physical chemistry. B
Dec 6, 2024
Methane emissions from livestock contribute to global warming. Seaweeds used as food additive offer a promising emission mitigation strategy because seaweeds are enriched in bromoform─a methanogenesis inhibitor. Therefore, understanding bromoform sto...
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