期刊
TALANTA
卷 100, 期 -, 页码 329-337出版社
ELSEVIER
DOI: 10.1016/j.talanta.2012.07.071
关键词
QSRR; Artificial neural networks; Antifungal agents; Azoles; HPLC
资金
- Ministry of Education and Science of the Republic of Serbia [172033]
Artificial neural network (ANN) is a learning system based on a computational technique which can simulate the neurological processing ability of the human brain. It was employed for building of the quantitative structure-retention relationships (QSRRs) model of antifungal agents-imidazoles or triazoles by structure. Computed molecular descriptors together with the percentage of acetonitrile in mobile phase (v/v) and buffer pH, being the most influential HPLC factors, were used as network inputs, giving the retention factor as model output. The multilayer perceptron network with a 9-5-1 topology was trained by using the back propagation algorithm. Good correlation between experimentally obtained data and ones predicted by using QSRR-ANN on previously unseen data sets indicates good predictive ability of the model. (C) 2012 Elsevier B.V. All rights reserved.
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