Predicting the rate at which a substance will pass through human skin and into the bloodstream is a problem of current interest. We use Gaussian Process modeling to train a set of predictors using every combination of six molecular features. We find that only three of the features are needed for our best predictor. This result could be useful in the further analysis of skin permeability.
|Title of host publication||IEEE International Joint Conference on Neural Networks (IJCNN) No. 11593964|
|Publisher||Institute of Electrical and Electronics Engineers (IEEE)|
|Publication status||Published - 2010|
- structure-permeability relationships