Automatic knowledge extraction from chemical structures: the case of mutagenicity prediction.

T. Ferrari, D. Cattaneo, G. Gini, N. Golbamaki Bakhtyari, A. Manganaro, E. Benfenati

Research output: Contribution to journalArticle

Abstract

This work proposes a new structure-activity relationship (SAR) approach to mine molecular fragments that act as structural alerts for biological activity. The entire process is designed to fit with human reasoning, not only to make the predictions more reliable but also to permit clear control by the user in order to meet customized requirements. This approach has been tested on the mutagenicity endpoint, showing marked prediction skills and, more interestingly, bringing to the surface much of the knowledge already collected in the literature as well as new evidence.

Original languageEnglish
Pages (from-to)365-383
Number of pages19
JournalSAR and QSAR in Environmental Research
Volume24
Issue number5
Publication statusPublished - 2013

ASJC Scopus subject areas

  • Molecular Medicine
  • Bioengineering
  • Drug Discovery
  • Medicine(all)

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  • Cite this

    Ferrari, T., Cattaneo, D., Gini, G., Golbamaki Bakhtyari, N., Manganaro, A., & Benfenati, E. (2013). Automatic knowledge extraction from chemical structures: the case of mutagenicity prediction. SAR and QSAR in Environmental Research, 24(5), 365-383.