Development of a Prediction Model for Mutagenicity - Validation of Ames Test Data

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  • Arakawa Masamoto
    Department of Business Administration, Ube National College of Technology
  • Funatsu Kimito
    Department of Chemical System Engineering, The University of Tokyo

Bibliographic Information

Other Title
  • 変異原性予測モデルの構築 - Ames試験データの検証

Description

We are developing a classification model for predicting mutagenicity of diverse organic compounds. We have proposed an ensemble model, in which many support vector machine models are constructed and integrated to predict mutagenicity. This model successfully predicted mutagenicity with accuracy rate of 79.6 %. However, on the other hand, the results of prediction suggested that some wrong data were included in database. Therefore, in this study, Ames test was carried out for some suspicious compounds. First, an ensemble model was constructed using the dataset that was assembled by Hansen et al. Then Ames test was carried out for five suspicious compounds that were registered in the database as negative. As a result, three of five compounds were judged as positive. This suggests that the database include some wrong data and our model can find these compounds efficiently.

Journal

  • Journal of Computer Aided Chemistry

    Journal of Computer Aided Chemistry 13 (0), 20-28, 2012

    Division of Chemical Information and Computer Sciences The Chemical Society of Japan

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