3.8 Article

Classification of Blood-Brain Barrier Permeation by Kohonen's Self-Organizing Neural Network (KohNN) and Support Vector Machine (SVM)

期刊

QSAR & COMBINATORIAL SCIENCE
卷 28, 期 9, 页码 989-994

出版社

WILEY-V C H VERLAG GMBH
DOI: 10.1002/qsar.200960008

关键词

Blood-brain barrier (BBB); Kohonen's self-organizing neural network (KohNN); Support vector machine (SVM); Medicinal chemistry; Drug design

资金

  1. National Natural Science Foundation of China [20605003]
  2. National High Tech Project [2006AA02Z337]
  3. SRF for ROCS
  4. Beijing University of Chemical Technology
  5. Molecular Networks GmbH, Erlangen, Germany

向作者/读者索取更多资源

Kohonen's self-organizing neural network (KohNN) method and support vector machine (SVM) classification method were used to build blood-brain barrier permeation prediction model, respectively. Based on five 2D property autocorrelation descriptors, several models have been built which were able to classify BBB penetration and nonpenetration compounds with the accuracy of over 96%.

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