AIMC Journal:
Journal of chemical information and modeling

Showing 351 to 360 of 934 articles

Recent Advances and Challenges in Protein Structure Prediction.

Journal of chemical information and modeling Dec 18, 2023
Artificial intelligence has made significant advances in the field of protein structure prediction in recent years. In particular, DeepMind's end-to-end model, AlphaFold2, has demonstrated the capability to predict three-dimensional structures of num...
Artificial Intelligence Research Design Drug Discovery Protein Folding
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SiSGC: A Drug Repositioning Prediction Model Based on Heterogeneous Simplifying Graph Convolution.

Journal of chemical information and modeling Dec 16, 2023
Drug repositioning plays a key role in disease treatment. With the large-scale chemical data increasing, many computational methods are utilized for drug-disease association prediction. However, most of the existing models neglect the positive influe...
Neural Networks, Computer Drug Repositioning
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Artificial Intelligence Agents for Materials Sciences.

Journal of chemical information and modeling Dec 12, 2023
The artificial intelligence (AI) tools based on large-language models may serve as a demonstration that we are reaching a groundbreaking new paradigm in which machines themselves will generate knowledge autonomously. This statement is based on the as...
Humans Artificial Intelligence Language Learning Research Personnel Materials Science
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Evaluating Machine Learning Methods of Analyzing Multiclass Metabolomics.

Journal of chemical information and modeling Dec 11, 2023
Multiclass metabolomic studies have become popular for revealing the differences in multiple stages of complex diseases, various lifestyles, or the effects of specific treatments. In multiclass metabolomics, there are multiple data manipulation steps...
Machine Learning Support Vector Machine Metabolomics
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From Black Boxes to Actionable Insights: A Perspective on Explainable Artificial Intelligence for Scientific Discovery.

Journal of chemical information and modeling Dec 11, 2023
The application of Explainable Artificial Intelligence (XAI) in the field of chemistry has garnered growing interest for its potential to justify the prediction of black-box machine learning models and provide actionable insights. We first survey a r...
Artificial Intelligence Machine Learning Language
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An Uncertainty-Guided Deep Learning Method Facilitates Rapid Screening of CYP3A4 Inhibitors.

Journal of chemical information and modeling Dec 6, 2023
Cytochrome P450 3A4 (CYP3A4), a prominent member of the P450 enzyme superfamily, plays a crucial role in metabolizing various xenobiotics, including over 50% of clinically significant drugs. Evaluating CYP3A4 inhibition before drug approval is essent...
Reproducibility of Results Deep Learning Drug Interactions Enzyme Inhibitors Cytochrome P-450 Enzyme System Cytochrome P-450 CYP3A Cytochrome P-450 CYP3A Inhibitors Uncertainty Cytochrome P-450 Enzyme Inhibitors
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Predicting Anti-inflammatory Peptides by Ensemble Machine Learning and Deep Learning.

Journal of chemical information and modeling Dec 6, 2023
Inflammation is a biological response to harmful stimuli, aiding in the maintenance of tissue homeostasis. However, excessive or persistent inflammation can precipitate a myriad of pathological conditions. Although current treatments such as NSAIDs, ...
Humans Machine Learning Algorithms Peptides Deep Learning Inflammation Anti-Inflammatory Agents
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A Multimodal Deep Learning Framework for Predicting PPI-Modulator Interactions.

Journal of chemical information and modeling Dec 1, 2023
Protein-protein interactions (PPIs) are essential for various biological processes and diseases. However, most existing computational methods for identifying PPI modulators require either target structure or reference modulators, which restricts thei...
Molecular Docking Simulation Deep Learning NF-E2-Related Factor 2 Protein Interaction Mapping Kelch-Like ECH-Associated Protein 1
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VGAE-MCTS: A New Molecular Generative Model Combining the Variational Graph Auto-Encoder and Monte Carlo Tree Search.

Journal of chemical information and modeling Nov 22, 2023
Molecular generation is crucial for advancing drug discovery, materials science, and chemical exploration. It expedites the search for new drug candidates, facilitates tailored material creation, and enhances our understanding of molecular diversity....
Artificial Intelligence Learning Drug Discovery Drug Development Monte Carlo Method
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Ensemble Geometric Deep Learning of Aqueous Solubility.

Journal of chemical information and modeling Nov 21, 2023
Geometric deep learning is one of the main workhorses for harnessing the power of big data to predict molecular properties such as aqueous solubility, which is key to the pharmacokinetic improvement of drug candidates. Two ensembles of graph neural n...
Neural Networks, Computer Deep Learning Water Solubility Thermodynamics
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