Data Mining of Toxic Chemicals and Database-Based Toxicity Prediction

Science Direct Working Paper No S1574-0331(04)70492-0

7 Pages Posted: 25 May 2017 Last revised: 23 Dec 2017

See all articles by Jiansuo Wang

Jiansuo Wang

Peking University - Institute of Physical Chemistry & College of Chemistry and Molecular Engineering

Luhua Lai

Peking University - Institute of Physical Chemistry & College of Chemistry and Molecular Engineering

Date Written: April 2001

Abstract

In the early stage of drug discovery, especially for computer-aided drug design, a large number of molecules will be proposed as potential leads and the bioactivity risk of these molecules is expected to be evaluated prior to synthesis. The rule-based expert systems have been used for the aim, while mining of a large amount of toxicological data can provide us with another promise. In the present study, we first make an initial analysis to a toxicological database of chemicals. Then a stepwise strategy is provided to data mine of toxic chemicals, which combines QSAR study with structure pattern clustering. Finally, on the basis of the analysis and aiming to be applied in the early stage of drug design, we propose one system as an alternative to toxicity prediction of chemicals, which is based on the database and dynamically combined with the database.

Keywords: toxic chemicals, data mining, toxicological database, toxicity prediction

Suggested Citation

Wang, Jiansuo and Lai, Luhua, Data Mining of Toxic Chemicals and Database-Based Toxicity Prediction (April 2001). Chemistry Preprint Archive Vol. 2001, Issue 4, pp 114-120. Available at SSRN: https://ssrn.com/abstract=2969534

Jiansuo Wang (Contact Author)

Peking University - Institute of Physical Chemistry & College of Chemistry and Molecular Engineering ( email )

Beijing, 100871
China

Luhua Lai

Peking University - Institute of Physical Chemistry & College of Chemistry and Molecular Engineering

Beijing, 100871
China

Register to save articles to
your library

Register

Paper statistics

Downloads
9
Abstract Views
101
PlumX Metrics