Rodent Carcinogenicity Dataset

Abstract

e rodent carcinogenicity dataset was compiled from the Carcinogenic Potency Database (CPDBAS) and was applied for the classi�cation of quantitative structure-activity relationship (QSAR) models for the prediction of carcinogenicity based on the counter-propagation arti�cial neural network (CP ANN) algorithm. e models were developed within EU-funded project CAESAR for regulatory use. e dataset contains the following information: common information about chemicals (ID, chemical name, and their CASRN), molecular structure information (SDF �les and SMILES), and carcinogenic (toxicological) properties information: carcinogenic potency (TD50_Rat_mg; carcinogen/noncarcinogen) and structural alert (SA) for carcinogenicity based on mechanistic data. Molecular structure information was used to get chemometrics information to calculate molecular descriptors (254 MDL and 784 Dragon descriptors), which were further used in predictive QSAR modeling. e dataset presented in the paper can be used in future research in oncology, ecology, or chemicals' risk assessment.