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Quantitative structure–retention relationships for mycotoxins and fungal metabolites in LC-MS/MS

✍ Scribed by Caihong Ji; Yanwei Li; Li Su; Xiaoyun Zhang; Xingguo Chen

Publisher
John Wiley and Sons
Year
2009
Tongue
English
Weight
424 KB
Volume
32
Category
Article
ISSN
1615-9306

No coin nor oath required. For personal study only.

✦ Synopsis

Abstract

Quantitative structure–retention relationship (QSRR) models were used to predict the retention time (t~R~) of mycotoxins and fungal metabolites. Heuristic method and radial basis function neural networks (RBFNN) were utilized to construct the linear and non‐linear QSRR models, respectively. The optimal QSRR model was developed based on a 5‐21‐1 RBFNN architecture using molecular descriptors calculated from molecular structure alone. The RBFNN model gave a square of correlation coefficient (R^2^) of 0.8709 and root mean square error of 1.2892 for the test set. This article provided a useful tool for predicting the t~R~ of other mycotoxins when experiment data are unknown.

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