AIMC Topic: Organic Chemicals

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Machine learning for toxicity characterization of organic chemical emissions using USEtox database: Learning the structure of the input space.

Environment international Jun 20, 2015
Toxicity characterization of chemical emissions in Life Cycle Assessment (LCA) is a complex task which usually proceeds via multimedia (fate, exposure and effect) models attached to models of dose-response relationships to assess the effects on targe...
Nonlinear Dynamics Linear Models Organic Chemicals Environmental Pollutants Humans Machine Learning
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Prediction of Henry's Law Constants via group-specific quantitative structure property relationships.

Chemosphere Jan 17, 2015
Henry's Law Constants (HLCs) for several hundred organic compounds in water at 25 °C were predicted by Quantitative Structure Property Relationship (QSPR) models, with the division of organic compounds into specific classes to yield more accurate mod...
Models, Theoretical Linear Models Quantitative Structure-Activity Relationship Gases Water Neural Networks, Computer Organic Chemicals
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TP-Transformer: An Interpretable Model for Predicting the Transformation Pathways of Organic Pollutants in Chemical Oxidation Processes.

Environmental science & technology Aug 5, 2025
Chemical oxidation is pivotal in remediating organic pollutants in aquatic systems; however, it frequently yields transformation products (TPs) with potential toxicological profiles surpassing those of the parent pollutants. Comprehensive identificat...
Organic Chemicals Water Pollutants, Chemical Oxidation-Reduction
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Predictive modeling and interpretability analysis of bioconcentration factors for organic chemicals in fish using machine learning.

Environmental pollution (Barking, Essex : 1987) Jul 15, 2025
Chemicals are misused and released into the environment, causing adverse effects on people and ecosystems. Assessing the potential environmental risks of these chemicals before their use is crucial. The bioconcentration factor (BCF) is a key paramete...
Machine Learning Bioaccumulation Animals Water Pollutants, Chemical Fishes Organic Chemicals Environmental Monitoring
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Structural Bias in Three-Dimensional Autoregressive Generative Machine Learning of Organic Molecules.

Journal of chemical information and modeling Jul 14, 2025
A range of generative machine learning models for the design of novel molecules and materials have been proposed in recent years. Models that can generate three-dimensional structures are particularly suitable for quantum chemistry workflows, enablin...
Organic Chemicals Molecular Structure Machine Learning
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Hyperbolic relational graph convolution networks plus: a simple but highly efficient QSAR-modeling method.

Briefings in bioinformatics Sep 2, 2021
Accurate predictions of druggability and bioactivities of compounds are desirable to reduce the high cost and time of drug discovery. After more than five decades of continuing developments, quantitative structure-activity relationship (QSAR) methods...
Neural Networks, Computer Artificial Intelligence Quantitative Structure-Activity Relationship Computer Graphics Organic Chemicals Computational Biology Molecular Structure Models, Chemical Drug Design Algorithms Drug Discovery Computer Simulation
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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...
Quantum Theory Monte Carlo Method Organic Chemicals p38 Mitogen-Activated Protein Kinases Thermodynamics Epoxide Hydrolases Machine Learning Software Protein Binding
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A Network Integration Method for Deciphering the Types of Metabolic Pathway of Chemicals with Heterogeneous Information.

Combinatorial chemistry & high throughput screening Jan 1, 2018
AIM AND OBJECTIVE: A metabolic pathway is an important type of biological pathway, which is composed of a series of chemical reactions. It provides essential molecules and energies for living organisms. To date, several metabolic pathways have been u...
Molecular Structure Metabolic Networks and Pathways Models, Molecular Support Vector Machine Structure-Activity Relationship Organic Chemicals Computational Biology
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Improve the biodegradability of post-hydrothermal liquefaction wastewater with ozone: conversion of phenols and N-heterocyclic compounds.

Water science and technology : a journal of the International Association on Water Pollution Research Apr 1, 2017
Hydrothermal liquefaction is a promising technology to convert wet biomass into bio-oil. However, post-hydrothermal liquefaction wastewater (PHWW) is also produced during the process. This wastewater contains a high concentration of organic compounds...
Hydroxyl Radical Heterocyclic Compounds Phenols Organic Chemicals Wastewater Ozone Bioreactors Water Pollutants, Chemical Biomass Kinetics
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