AIMC Journal:
Journal of chemical information and modeling

Showing 371 to 380 of 934 articles

Prediction of Cytochrome P450 Inhibition Using a Deep Learning Approach and Substructure Pattern Recognition.

Journal of chemical information and modeling Oct 21, 2023
Cytochrome P450 (CYP) is a family of enzymes that are responsible for about 75% of all metabolic reactions. Among them, CYP1A2, CYP2C9, CYP2C19, CYP2D6, and CYP3A4 participate in the metabolism of most drugs and mediate many adverse drug reactions. T...
Deep Learning Microsomes, Liver Cytochrome P-450 Enzyme System Cytochrome P-450 CYP3A Protein Isoforms Cytochrome P-450 CYP2C19 Cytochrome P-450 CYP2C9 Cytochrome P-450 Enzyme Inhibitors Cytochrome P-450 CYP2D6 Cytochrome P-450 CYP1A2
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Efficient Exploration of Chemical Compound Space Using Active Learning for Prediction of Thermodynamic Properties of Alkane Molecules.

Journal of chemical information and modeling Oct 19, 2023
We introduce an exploratory active learning (AL) algorithm using Gaussian process regression and marginalized graph kernel (GPR-MGK) to sample chemical compound space (CCS) at minimal cost. Targeting 251,728 enumerated alkane molecules with 4-19 carb...
Neural Networks, Computer Algorithms Molecular Structure Thermodynamics Alkanes
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A Comparative Analysis of Data Synthesis Techniques to Improve Classification Accuracy of Raman Spectroscopy Data.

Journal of chemical information and modeling Oct 11, 2023
Raman spectra are examples of high dimensional data that can often be limited in the number of samples. This is a primary concern when Deep Learning frameworks are developed for tasks such as chemical species identification, quantification, and diagn...
Neural Networks, Computer Machine Learning Algorithms Spectrum Analysis, Raman
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Recent Studies of Artificial Intelligence on Drug Absorption.

Journal of chemical information and modeling Oct 11, 2023
Absorption is an important area of research in pharmacochemistry and drug development, because the drug has to be absorbed before any drug effects can occur. Furthermore, the ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) profi...
Artificial Intelligence Databases, Factual Drug Discovery Chemical Phenomena
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Swarm Smart Meta-Estimator for 2D/2D Heterostructure Design.

Journal of chemical information and modeling Oct 5, 2023
Two-dimensional (2D) semiconductors are central to many scientific fields. The combination of two semiconductors (heterostructure) is a good way to lift many technological deadlocks. Although ab initio calculations are useful to study physical proper...
Machine Learning Algorithms Cluster Analysis
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E2EDA: Protein Domain Assembly Based on End-to-End Deep Learning.

Journal of chemical information and modeling Oct 3, 2023
With the development of deep learning, almost all single-domain proteins can be predicted at experimental resolution. However, the structure prediction of multi-domain proteins remains a challenge. Achieving end-to-end protein domain assembly and fur...
Deep Learning Proteins Protein Domains
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Applications and Advances in Machine Learning Force Fields.

Journal of chemical information and modeling Sep 26, 2023
Force fields (FFs) form the basis of molecular simulations and have significant implications in diverse fields such as materials science, chemistry, physics, and biology. A suitable FF is required to accurately describe system properties. However, an...
Machine Learning Physics
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DASH: Dynamic Attention-Based Substructure Hierarchy for Partial Charge Assignment.

Journal of chemical information and modeling Sep 22, 2023
We present a robust and computationally efficient approach for assigning partial charges of atoms in molecules. The method is based on a hierarchical tree constructed from attention values extracted from a graph neural network (GNN), which was traine...
Neural Networks, Computer Quantum Theory
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ReactionDataExtractor 2.0: A Deep Learning Approach for Data Extraction from Chemical Reaction Schemes.

Journal of chemical information and modeling Sep 20, 2023
Knowledge in the chemical domain is often disseminated graphically via chemical reaction schemes. The task of describing chemical transformations is greatly simplified by introducing reaction schemes that are composed of chemical diagrams and symbols...
Neural Networks, Computer Artificial Intelligence Deep Learning
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MIST-CF: Chemical Formula Inference from Tandem Mass Spectra.

Journal of chemical information and modeling Sep 19, 2023
Chemical formula annotation for tandem mass spectrometry (MS/MS) data is the first step toward structurally elucidating unknown metabolites. While great strides have been made toward solving this problem, the current state-of-the-art method depends o...
Neural Networks, Computer Databases, Factual Tandem Mass Spectrometry
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