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RosENet: Improving binding affinity prediction by leveraging molecular mechanics energies with a 3D Convolutional Neural Network
Hussein Hassan-Harrirou, Ce Zhang, View ORCID ProfileThomas Lemmin
doi: https://doi.org/10.1101/2020.05.12.090191
Hussein Hassan-Harrirou
1DS3Lab, System Group, Department of Computer Sciences, ETH Zurich, CH-8092 Zurich, Switzerland
Ce Zhang
1DS3Lab, System Group, Department of Computer Sciences, ETH Zurich, CH-8092 Zurich, Switzerland
Thomas Lemmin
1DS3Lab, System Group, Department of Computer Sciences, ETH Zurich, CH-8092 Zurich, Switzerland
2Institute of Medical Virology, University of Zurich (UZH), CH-8057 Zurich, Switzerland
Posted May 14, 2020.
RosENet: Improving binding affinity prediction by leveraging molecular mechanics energies with a 3D Convolutional Neural Network
Hussein Hassan-Harrirou, Ce Zhang, Thomas Lemmin
bioRxiv 2020.05.12.090191; doi: https://doi.org/10.1101/2020.05.12.090191
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