The importance of scaling in data mining for toxicity prediction.

Description

No / While mining a data set of 554 chemicals in order to extract information on their toxicity value, we faced the problem of scaling all the data. There are numerous different approaches to this procedure, and in most cases the choice greatly influences the results. The aim of this paper is 2-fold. First, we propose a universal scaling procedure for acute toxicity in fish according to the Directive 92/32/EEC. Second, we look at how expert preprocessing of the data effects the performance of qualitative structure-activity relationship (QSAR) approach to toxicity prediction.

Links & Downloads

1. Mazzatorta, P. Benfenati, E., Neagu, D.C. and Gini, G. (2002). The importance of scaling in data mining for toxicity prediction. Journal of Chemical Information and Computer Sciences. Vol. 4, No. 5, pp. 1250-1255.
2. http://hdl.handle.net/10454/3594
3. https://doi.org/10.1021/ci025520n

Tags

Data mining

Scaling

QSAR

Chemicals toxicity

Additional Fields

Identifer	oai:union.ndltd.org:BRADFORD/oai:bradscholars.brad.ac.uk:10454/3594
Date	January 2002
Creators	Mazzatorta, P., Benfenati, E., Neagu, Daniel, Gini, G.
Source Sets	Bradford Scholars
Language	English
Detected Language	English
Type	Article, No full-text available in the repository