Data mining on carcinogenicity of chemical compounds by the JSM method

Autor:	M. Vrachko, V. G. Blinova, M. Novich, N. Fedorova, N. V. Kharchevnikova, D. A. Dobrynin
Rok vydání:	2009
Předmět:	Data presentation Environmental science Data mining computer.software_genre General Economics Econometrics and Finance computer Carcinogen
Zdroj:	Automatic Documentation and Mathematical Linguistics. 43:330-335
ISSN:	1934-8371 0005-1055
DOI:	10.3103/s000510550906003x
Popis:	Prediction of the carcinogenicity of chemical compounds to rats was carried out by data mining analysis based on the logic of John Stuart Mill (JSM) and the fragmentary code of the substructure superposition (FCSS) data presentation language. The learning (608 compounds) and test (156 compounds) samples were taken from the database on the carcinogenicity of substances for laboratory animals developed by the Environmental Protection Agency of the USA (EPA USA). Predictions were made for 44% of the test samples. The prediction accuracy was 71%, sensitivity 73%, and specificity 67%. The causes for erroneous positive and negative predictions were studied, accounting for bioactivation of compounds in the course of metabolic biotransformations.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::46b1e9f2b1daa12217d3cb958c536da7 https://doi.org/10.3103/s000510550906003x Zobrazit plný text záznamu Full text from SpringerLink