Science Inventory

Understanding Genetic Toxicity Through Data Mining: The Process of Building Knowledge by Integrating Multiple Genetic Toxicity Databases

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).

Impact/Purpose:

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.

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.

Record Details:

Record Type:DOCUMENT( JOURNAL/ PEER REVIEWED JOURNAL)
Product Published Date:02/01/2008
Record Last Revised:12/04/2008
OMB Category:Other
Record ID: 195204