Yi will be discussing feature selection modelling for percutaneous absorption across Synthetic membranes
Abstract is below:
Predicting the rate of percutaneous absorption across mammalian and artificial membranes is a complex problem. Different machine learning models have been used in previous studies, and results show that Gaussian processes provided the best result, based on a range of statistical measures. In the current study, a dataset of synthetic (Polydimethylsiloxane, PDMS) membranes, containing so many descriptors, is considered. One of the main purposes of the study is to use feature selection methods to select a set of molecular properties that exert the most important influence on percutaneous absorption across PDMS membranes, in the hope that this will better inform studies on human skin.