Predicting reversed-phase liquid chromatographic retention times of pesticides by deep neural networks

To be able to predict reversed phase liquid chromatographic (RPLC) retention times of contaminants is an asset in order to solve food contamination issues. The development of quantitative structure–retention relationship models (QSRR) requires selection of the best molecular descriptors and machine-...

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Xehetasun bibliografikoak

Egile nagusia:	Julien Parinet
Formatua:	Artigo
Hizkuntza:	Inglês
Argitaratua:	Elsevier 2021-12-01
Saila:	Heliyon
Gaiak:	Pesticides QSRR Molecular descriptors Deep neural network Reversed-phase liquid chromatography Selection of inputs
Sarrera elektronikoa:	http://www.sciencedirect.com/science/article/pii/S2405844021026669
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