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Molecule generation is a challenging open problem in cheminformatics.
SMILES, a chemical language and information system. 1. introduction to methodology and encoding rules
D. Weininger · 1988
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A learning algorithm for continually running fully recurrent neural networks
R. J. Williams and D. Zipser · 1989
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Finding structure in time
J. L. Elman · 1990
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Fragment-Based Drug Discovery
D. A. Erlanson, R. S. McDowell, and T. O’Brien · 2004
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ZINC – A Free Database of Commercially Available Compounds for Virtual Screening
J. J. Irwin and B. K. Shoichet · 2005
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On the Art of Compiling and Using ’Drug-Like’ Chemical Fragment Spaces
J. Degen, C. Wegscheid-Gerlach, A. Zaliani, et al · 2008
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Estimation of synthetic accessibility score of drug-like molecules based on molecular complexity and fragment contributions
P. Ertl and A. Schuffenhauer · 2009
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Neural Network for Graphs: A Contextual Constructive Approach
A. Micheli · 2009
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The Graph Neural Network Model
F. Scarselli, M. Gori, A. C. Tsoi, et al · 2009
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Generating text with recurrent neural networks
I. Sutskever, J. Martens, and G. Hinton · 2011
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Quantifying the chemical beauty of drugs
G. R. J. Bickerton, G. V. Paolini, J. Besnard, et al · 2012
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Fragment Based Drug Design: From Experimental to Computational Approaches
A. Kumar, A. Voet, and K. Y. J. Zhang · 2012
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Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation
K. Cho, B. van Merriënboer, Ç. Gülçehre, et al · 2014
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Generative adversarial nets
I. Goodfellow, J. Pouget-Abadie, M. Mirza, et al · 2014
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Auto-Encoding Variational Bayes
D. P. Kigma and M. Welling · 2014
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Distributed Representations of Sentences and Documents
Q. V. Le and T. Mikolov · 2014
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Quantum chemistry structures and properties of 134 kilo molecules
R. Ramakrishnan, P. O. Dral, M. Rupp, et al · 2014
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Grammar Variational Autoencoder
M. J. Kusner, B. Paige, and J. M. Hernández-Lobato · 2017
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Syntax-directed variational autoencoder for structured data
H. Dai, Y. Tian, B. Dai, et al · 2018
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Automatic Chemical Design Using a Data-Driven Continuous Representation of Molecules
R. Gómez-Bombarelli, J. N. Wei, D. Duvenaud, et al · 2018
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Junction Tree Variational Autoencoder for Molecular Graph Generation
W. Jin, R. Barzilay, and T. S. Jakkola · 2018
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Constrained Graph Variational Autoencoders for Molecule Design
Q. Liu, M. Allamanis, M. Brockschmidt, et al · 2018
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Generating Sentences from a Continuous Space
S. R. Bowman, L. Vilnis, O. Vinyals, Andrew Dai, et al · 2016
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PubChem BioAssay: 2017 update
A. Gindulyte, B. A. Shoemaker, J. Zhang, et al · 2016
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Gated graph sequence neural networks
Y. Li, R. Zemel, M. Brockschmidt, et al · 2016
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Fragment-Based Lead Discovery
B. J. Davis and S. D. Roughley · 2017
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B. Samanta, A. De De, G. Jana, et al · 2018
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GraphVAE: Towards Generation of Small Graphs Using Variational Autoencoders
M. Simonovsky and N. Komodakis · 2018
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Graphrnn: Generating realistic graphs with deep auto-regressive models
J. You, R. Ying, X. Ren, et al · 2018
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Deep learning for molecular generation
Y. Xu, K. Lin, S. Wang, et al · 2019
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Edge-based sequential graph generation with recurrent neural networks
D. Bacciu, A. Micheli, and M. Podda · 2020
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