Mathematical deep learning for pose and binding affinity prediction and ranking in D3R Grand Challenges

@article{Nguyen2018MathematicalDL,
  title={Mathematical deep learning for pose and binding affinity prediction and ranking in D3R Grand Challenges},
  author={Duc Duy Nguyen and Zixuan Cang and Kedi Wu and Menglun Wang and Yin Cao and Guowei Wei},
  journal={Journal of Computer-Aided Molecular Design},
  year={2018},
  volume={33},
  pages={71-82}
}
Advanced mathematics, such as multiscale weighted colored subgraph and element specific persistent homology, and machine learning including deep neural networks were integrated to construct mathematical deep learning models for pose and binding affinity prediction and ranking in the last two D3R Grand Challenges in computer-aided drug design and discovery. D3R Grand Challenge 2 focused on the pose prediction, binding affinity ranking and free energy prediction for Farnesoid X receptor ligands… 
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