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References (29)
-
M Hartenfeller, G Schneider (2011)
Enabling future drug discovery by de novo design, 1
-
JH Jensen (2019)
A graph?based genetic algorithm and generative model/Monte Carlo tree search for the exploration of chemical space, 10
-
Mariya Popova, Olexandr Isayev, Alexander Tropsha (2018)
Deep reinforcement learning for de novo drug design, 4
-
D Weininger (1988)
SMILES, a chemical language and information system, 28
-
EW Dijkstra (1982)
Selected writings on Computing: A Personal Perspective -
WK Hastings (1970)
Monte Carlo sampling methods using Markov chains and their applications, 57
-
M Olivecrona, T Blaschke, O Engkvist, H Chen (2017)
Molecular de?novo design through deep reinforcement learning, 9
-
PS Kutchukian, NY Vasilyeva, J Xu (2012)
Inside the mind of a medicinal chemist: the role of human bias in compound prioritization during drug discovery, 7
-
H Altae‐Tran, B Ramsundar, AS Pappu, V Pande (2017)
Low data drug discovery with one?shot learning, 3
-
JS Bergstra, R Bardenet, Y Bengio, B Kégl (2011)
Algorithms for hyper?parameter optimization, 9
-
Peter Ertl, Richard Lewis (2012)
IADE: a system for intelligent automatic design of bioisosteric analogs, 26
-
J Arús‐Pous, T Blaschke, S Ulander, J‐L Reymond, H Chen, O Engkvist (2019)
Exploring the GDB?13 chemical space using deep generative models, 11
-
U Lessel, C Lemmen (2019)
Comparison of large chemical spaces, 10
-
J Degen, C Wegscheid‐Gerlach, A Zaliani, M Rarey (2008)
On the art of compiling and using ?drug?like? chemical fragment spaces, 3
-
Gabriel Lima Guimaraes, Benjamin Sanchez‐Lengeling, Carlos Outeiral, Pedro Luis Cunha Farias, Alán Aspuru‐Guzik (2018)
Objective?Reinforced Generative Adversarial Networks (ORGAN) for Sequence Generation Models, 1705.10843
-
DVS Green, S Pickett, C Luscombe (2019)
BRADSHAW: a system for automated molecular design, 34
-
N Brown, B McKay, F Gilardoni, J Gasteiger (2004)
A graph?based genetic algorithm and its application to the multiobjective evolution of median molecules, 44
-
PG Polishchuk, TI Madzhidov, A Varnek (2013)
Estimation of the size of drug?like chemical space based on GDB?17 data, 27
-
F Grisoni, M Moret, R Lingwood, G Schneider (2020)
Bidirectional molecule generation with recurrent neural networks, 60
-
Yaxia Yuan, Jianfeng Pei, Luhua Lai (2011)
LigBuilder 2: A Practical de Novo Drug Design Approach, 51
-
R Winter, F Montanari, A Steffen, H Briem, F Noé, D‐A Clevert (2019)
Efficient multi?objective molecular optimization in a continuous latent space, 10
-
A Zhavoronkov, YA Ivanenkov, A Aliper (2019)
Deep learning enables rapid identification of potent DDR1 kinase inhibitors, 37
-
A Kadurin, SI Nikolenko, K Khrabrov, A Aliper, A Zhavoronkov (2017)
druGAN: an advanced generative adversarial autoencoder model for de novo generation of new molecules with desired molecular properties in silico, 14
-
P Renz, RD Van, JK Wegner, S Hochreiter, G Klambauer (2020)
On failure modes in molecule generation and optimization -
Daniil Polykovskiy, Alexander Zhebrak, Benjamin Sanchez‐Lengeling, Sergey Golovanov, Oktai Tatanov, Stanislav Belyaev, Rauf Kurbanov, Aleksey Artamonov, Vladimir Aladinskiy, Mark Veselov, Artur Kadurin, Simon Johansson, Hongming Chen, Sergey Nikolenko, Alan Aspuru‐Guzik, Alex Zhavoronkov (2018)
Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models -
Rafael Gómez‐Bombarelli, Jennifer N. Wei, David Duvenaud, José Miguel Hernández‐Lobato, Benjamín Sánchez‐Lengeling, Dennis Sheberla, Jorge Aguilera‐Iparraguirre, Timothy D. Hirzel, Ryan P. Adams, Alán Aspuru‐Guzik (2018)
Automatic Chemical Design Using a Data?Driven Continuous Representation of Molecules, 4
-
AM Virshup, J Contreras‐García, P Wipf, W Yang, DN Beratan (2013)
Stochastic voyages into uncharted chemical space produce a representative library of all possible drug?like compounds, 135
-
P Polishchuk (2020)
CReM: chemically reasonable mutations framework for structure generation, 12
-
N Brown, M Fiscato, MHS Segler, AC Vaucher (2019)
GuacaMol: benchmarking models for de novo molecular design, 59
- Publisher
- Wiley
- Copyright
- © 2020 The Authors. Applied AI Letters published by John Wiley & Sons Ltd
- eISSN
- 2689-5595
- DOI
- 10.1002/ail2.17
- Publisher site
- See Article on Publisher Site
Abstract
Journal
Applied AI Letters – Wiley
Published: Dec 1, 2020