Discriminant Function Analyses of Liver-Specific Carcinogens

نویسندگان

  • Richard D. Beger
  • John F. Young
  • Hong Fang
چکیده

The ability to predict organ-specific carcinogenicity would aid FDA reviewers in evaluating new chemical applications. A NCTR liver cancer database (NCTRlcdb) containing 999 compounds has been developed with three sets of descriptors. The NCTRlcdb has Cerius2, Molconn-Z, and (13)C NMR descriptors for each compound. Each compound in the database was assigned a liver cancer or a nonliver cancer classification. Compounds within the NCTRlcdb were evaluated for liver-specific carcinogenicity using partial least squares principal component discriminant function (PLS-DF) modeling. PLS-DF models based on estimated a priori classification probabilities of 0.29 for liver cancer and 0.71 for noncancer yielded an overall predictability of 70.6% which was comprised of a liver cancer sensitivity of 18.8% and a noncancer specificity of 90.8%. PLS-DF models based on equal a priori classification probabilities, 0.50 for liver cancer and 0.5 for noncancer, yielded an overall predictability of 61.0% which was comprised of a liver cancer sensitivity of 50.5% and a noncancer specificity of 65.3%.

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عنوان ژورنال:
  • Journal of chemical information and computer sciences

دوره 44 3  شماره 

صفحات  -

تاریخ انتشار 2004