ArticleEnvironmental science and pollution research international2020
The using of the Index of Ideality of Correlation (IIC) to improve predictive potential of models of water solubility for pesticides.
Article in Environmental science and pollution research international, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed.
- A simple and reliable QSPR model for prediction of chromatography retention indices of volatile organic compounds in peppers.RSC advances · 2024Article
- A regression-based QSAR-model to predict acute toxicity of aromatic chemicals in tadpoles of the Japanese brown frog (Rana japonica): Calibration, validation, and future developments to support risk assessment of chemicals in amphibians.The Science of the total environment · 2022Article
- The Monte Carlo approach to model and predict the melting point of imidazolium ionic liquids using hybrid optimal descriptors.RSC advances · 2021Article
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5 authors.
Funding
Abstract
Models for water solubility of pesticides suggested in this manuscript are important data from point of view of ecologic engineering. The Index of Ideality of Correlation (IIC) of groups of quantitative structure-property relationships (QSPRs) for water solubility of pesticides related to the calibration sets was used to identify good in silico models. This comparison confirmed the high IIC set provides better statistical quality of the model for the validation set. Though there are large databases on solubility, the reliable prediction of the endpoint for new substances which are potential pesticides is an important ecologic task. Unfortunately, predictive models for various endpoints suffer overtraining, and the IIC serves to avoid or at least reduce this. Thus, the approach suggested has both theoretical and economic effects for ecology.
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