Bioinformatics Vol. 19 no. 10 2003
Pages 1179-1182
© 2003 Oxford University Press
A survey of the Predictive Toxicology Challenge 2000–2001
Machine Learning Lab, University Freiburg, D-79110 Freiburg, Germany
Received on May 10, 2002
; revised on October 15, 2002
; accepted on October 18, 2002
Motivation: The Predictive Toxicology Challenge (PTC) was initiated to stimulate the development of advanced techniques for predictive toxicology models. The goal of this challenge was to compare different approaches for the prediction of rodent carcinogenicity, based on the experimental results of the US National Toxicology Program (NTP).
Results: 111 sets of predictions for 185 compounds have been evaluated on quantitative and qualitative scales to select the most predictive models and those with the highest toxicological relevance. The accuracy of the submitted predictions was between 25 and 79 %. An evaluation of the most accurate models by toxicological experts showed, that it is still hard for domain experts to interpret the submitted models and to put them into relation with toxicological knowledge.
Availability: PTC details and data can be found at: http://www.predictive-toxicology.org/ptc/
Contact: helma{at}informatik.uni-freiburg.de
* To whom correspondence should be addressed.
Present address: Institute for
Computer Science, Technical University Munich, D-85748, Garching,
Germany.
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