Improving AutoDock Vina Using Random Forest: The Growing Accuracy of Binding Affinity Prediction by the Effective Exploitation of Larger Data Sets

By Hongjian Li, K. Leung, Man-Hon Wong, Pedro J. Ballester. 2015

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TopologyNet: Topology based deep convolutional and multi-task neural networks for biomolecular property predictions (2017, unknown): “The persistent homology analysis performed in this application is summarized in Except for the result of our TNet-BP, all other results are adopted from Li et al .”
Performance of machine-learning scoring functions in structure-based virtual screening (2017, methodology): “For example, in building RF-Score v3 for binding affinity prediction, no overlapping between training and test sets is permitted by construction 12 .”
Key Topics in Molecular Docking for Drug Design (2019, methodology): “In fact, it has been shown that increasing the size of the training set boosts the scoring function’s performance [82,172,183].”