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Understanding Genetic Toxicity Through Data Mining: The Process of Building Knowledge by Integrating Multiple Genetic Toxicity Databases
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Citation:
Yang, C., C. H. Hasselgren, S. Boyer, K. Arvidson, S. Aveston, P. Diekes, R. Benigni, R. D. Benz, J. Contrera, N. L. Kruhlak, E. J. Matthews, X. Han, J. Jaworska, R. A. Kemper, J. F. Rathman, AND A. M. RICHARD. Understanding Genetic Toxicity Through Data Mining: The Process of Building Knowledge by Integrating Multiple Genetic Toxicity Databases . Toxicology Mechanisms and Methods. Taylor & Francis, Inc., Philadelphia, PA, 18(2 & 3):277-295, (2008).Description:
This paper demonstrates the usefulness of representing a chemical by its structural features and the use of these features to profile a battery of tests rather than relying on a single toxicity test of a given chemical. This paper presents data mining/profiling methods applied in a weight-of-evidence approach to assess potential for genetic toxicity, and to guide the development of intelligent testing strategies.
Purpose/Objective:
This paper demonstrates the usefulness of representing a chemical by its structural features and the use of these features to profile a battery of tests rather than relying on a single toxicity test of a given chemical. This paper presents data mining/profiling methods applied in a weight-of-evidence approach to assess potential for genetic toxicity, and to guide the development of intelligent testing strategies.
Record Details:
Record Type: DOCUMENT (JOURNAL/PEER REVIEWED JOURNAL)Organization:
U.S. ENVIRONMENTAL PROTECTION AGENCYOFFICE OF RESEARCH AND DEVELOPMENT
NATIONAL CENTER FOR COMPUTATIONAL TOXICOLOGY