DeepAutoQSAR

DeepAutoQSAR is a machine learning (ML) solution that allows users to predict molecular properties based on chemical structure. The automated supervised learning pipeline enables both novice and experienced users to train and inference best-in-class quantitative structure activity/property relationship (QSAR/QSPR) models.

 

DeepAutoQSAR methods are designed to efficiently handle data sets of tens or hundreds of thousands of structures, where the traditional methods in the AutoQSAR are useful up to a few thousand structures in the training set. DeepAutoQSAR gives similar results to AutoQSAR for the same size data sets, but is superior for larger sizes. For more information on DeepAutoQSAR, see DeepAutoQSAR: Scalable, Intuitive, Deep-learning QSAR models for Big Data Applications.

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