Development of CYP3A4 inhibition models: comparisons of machine-learning techniques and molecular descriptors.

@article{Arimoto2005DevelopmentOC,
  title={Development of CYP3A4 inhibition models: comparisons of machine-learning techniques and molecular descriptors.},
  author={Rieko Arimoto and Madhu-Ashni Prasad and Eric M. Gifford},
  journal={Journal of biomolecular screening},
  year={2005},
  volume={10 3},
  pages={197-205}
}
Computational models of cytochrome P450 3A4 inhibition were developed based on high-throughput screening data for 4470 proprietary compounds. Multiple models differentiating inhibitors (IC(50) <3 microM) and noninhibitors were generated using various machine-learning algorithms (recursive partitioning [RP], Bayesian classifier, logistic regression, k-nearest-neighbor, and support vector machine [SVM]) with structural fingerprints and topological indices. Nineteen models were evaluated by… CONTINUE READING
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Keseru GM: A neural network based virtual screening of cytochrome p450 3A4 inhibitors

  • L Molnar
  • Bioorg Med Chem Lett 2002;12:419-421. Arimoto et…
  • 2005
1 Excerpt

Ensemble learning

  • TG Dietterich
  • In Arbib MA (ed): The Handbook of Brain Theory…
  • 2003
1 Excerpt

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