Development of a QSAR model to predict molecular inhibition of human STAT3
Joshua M. PattersoniD, Kimberly A. Milligan, Cherese Winstead
Abstract
Herein is described a method to develop a QSAR model to predict the molecular inhibition of human STAT3. The model was built using machine learning using Python 3.3. A random forest machine learning algorithm was deployed. The model produced a R2 value of 0.86, indicating that our QSAR model is effective at predicting inhibitory compounds of STAT3.
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