Improvement on Generative Adversarial Network for Targeted Drug Design
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[1] Ola Engkvist,et al. A de novo molecular generation method using latent vector based generative adversarial network , 2019, J. Cheminformatics.
[2] Gisbert Schneider,et al. Computer-based de novo design of drug-like molecules , 2005, Nature Reviews Drug Discovery.
[3] Thomas Blaschke,et al. Application of Generative Autoencoder in De Novo Molecular Design , 2017, Molecular informatics.
[4] Aaron C. Courville,et al. Improved Training of Wasserstein GANs , 2017, NIPS.
[5] Jun Xu,et al. QBMG: quasi-biogenic molecule generator with deep recurrent neural network , 2019, Journal of Cheminformatics.
[6] Alán Aspuru-Guzik,et al. Automatic Chemical Design Using a Data-Driven Continuous Representation of Molecules , 2016, ACS central science.
[7] Alexandre Varnek,et al. Estimation of the size of drug-like chemical space based on GDB-17 data , 2013, Journal of Computer-Aided Molecular Design.
[8] Yoshua Bengio,et al. Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation , 2014, EMNLP.
[9] Sandeep Sinha,et al. Drug Discovery and Development , 2018 .
[10] Alán Aspuru-Guzik,et al. Objective-Reinforced Generative Adversarial Networks (ORGAN) for Sequence Generation Models , 2017, ArXiv.