Predicting Blood-Brain Barrier Penetration by Stochastic Discrimination
Dechang Chen, Jianwen Fang, Jiawei Yu · 2008
The importance of optimizing the ability to penetrate blood-brain barrier of potential drug candidates is now widely recognized. Accurate computational prediction of such a properly will significantly enhance the speed of the blood-brain barrier penetration analysis and reduce the cost of drug discovery. In this paper, we present some results of our predictive model built on the stochastic discrimination, a pattern classification method that has been shown to be a useful in the literature.