PTML-ANN Model for Simultaneous Prediction of Cytotoxic and Ecotoxic Effect of Nanoparticles

A. Speck-Planche, V. V. Kleandrova
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Abstract

Biological data on the cytotoxic and the ecotoxic effects of coated and uncoated nanoparticles were retrieved from the scientific literature. The mathematical treatment of these data was based on the use of perturbation theory (PT) operators. This enabled the development of a model that combined perturbation theory concepts with artificial neural networks (PTML-ANN). New nanoparticles not reported during the generation of the PTML-ANN model were used in a virtual screening experiment. For these new nanoparticles, the predictions performed by the PTML-ANN model converged with the experimental results.
纳米颗粒细胞毒性和生态毒性同时预测的PTML-ANN模型
从科学文献中检索了包被和未包被纳米颗粒的细胞毒性和生态毒性作用的生物学数据。这些数据的数学处理是基于使用微扰理论(PT)算子。这使得将微扰理论概念与人工神经网络(PTML-ANN)相结合的模型得以发展。在PTML-ANN模型生成过程中未报道的新纳米颗粒被用于虚拟筛选实验。对于这些新型纳米粒子,PTML-ANN模型的预测结果与实验结果趋于一致。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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