Modeling acute toxicity of chemicals to Daphnia magna: A probabilistic neural network approach

1 February 2001

journal article
hazard risk-assessment
Published by Oxford University Press (OUP) in Environmental Toxicology and Chemistry

Vol. 20 (2) , 420-431
https://doi.org/10.1002/etc.5620200225

Abstract

A methodology based on probabilistic neural networks (PNNs) is applied to model the acute toxicity (48‐h LC50) of a set of 700 highly diverse chemicals to Daphnia magna. First, cross‐validation experiments confirming the potential use of the PNN as modeling tool for the problem at hand were performed. Next, various approaches to construct‐improved models are presented. The resulting four models are then validated using an external test set of 76 additional compounds. Input to the PNNs is derived solely from simple molecular descriptors and structural fragments and excludes bulk property parameters, such as the water solubility or the octanol/water partition coefficient.

Keywords

This publication has 11 references indexed in Scilit:

Modeling the Toxicity of Chemicals to Tetrahymena pyriformis Using Molecular Fragment Descriptors and Probabilistic Neural Networks
Archives of Environmental Contamination and Toxicology, 2000
Using probabilistic neural networks to model the toxicity of chemicals to the fathead minnow (Pimephales promelas): A study based on 865 compounds
Chemosphere, 1999
Short Communication: A Note of Caution to Users of ECOSAR
Water Quality Research Journal, 1999
Influence of Data Preprocessing and Kernel Selection on Probabilistic Neural Network Modeling of the Acute Toxicity of Chemicals to the Fathead Minnow and Vibrio fischeri Bacteria
Water Quality Research Journal, 1998
Classification of Environmentally Occurring Chemicals Using Structural Fragments and PLS Discriminant Analysis
Environmental Science & Technology, 1997
PREDICTING MODES OF TOXIC ACTION FROM CHEMICAL STRUCTURE: ACUTE TOXICITY IN THE FATHEAD MINNOW (PIMEPHALES PROMELAS)
Environmental Toxicology and Chemistry, 1997
Classifying environmental pollutants
Chemosphere, 1992
Probabilistic neural networks
Neural Networks, 1990
Estimation of a multivariate density
Annals of the Institute of Statistical Mathematics, 1966
On Estimation of a Probability Density Function and Mode
The Annals of Mathematical Statistics, 1962