A joint optimization QSAR model of fathead minnow acute toxicity based on a radial basis function neural network and its consensus modeling.

ABSTRACT: Acute toxicity of the fathead minnow (Pimephales promelas) is an important indicator to evaluate the hazards and risks of compounds in aquatic environments. The aim of our study is to explore the predictive power of the quantitative structure-activity relationship (QSAR) model based on a radial basis function (RBF) neural network with the joint optimization method to study the acute toxicity mechanism, and to develop a potential acute toxicity prediction model, for fathead minnow. To ensure the symmetry and fairness of the data splitting and to generate multiple chemically diverse training and validation sets, we used a self-organizing mapping (SOM) neural network to split the modeling dataset (containing 955 compounds) characterized by PaDEL-descriptors. After preliminary selection

SUBMITTER: Wang Y 

PROVIDER: S-EPMC9054390 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature