In:
Environmental Toxicology and Chemistry, Wiley, Vol. 20, No. 2 ( 2001-02), p. 420-431
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.
Type of Medium:
Online Resource
ISSN:
0730-7268
,
1552-8618
DOI:
10.1002/etc.5620200225
Language:
English
Publisher:
Wiley
Publication Date:
2001
detail.hit.zdb_id:
2027441-5
SSG:
12