A citation-based method for searching scientific literature

Marwin H S Segler, Thierry Kogej, Christian Tyrchan, Mark P Waller. ACS Cent Sci 2018
Times Cited: 284







List of co-cited articles
887 articles co-cited >1



Times Cited
  Times     Co-cited
Similarity


Automatic Chemical Design Using a Data-Driven Continuous Representation of Molecules.
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. ACS Cent Sci 2018
459
61

Molecular de-novo design through deep reinforcement learning.
Marcus Olivecrona, Thomas Blaschke, Ola Engkvist, Hongming Chen. J Cheminform 2017
200
41

Deep reinforcement learning for de novo drug design.
Mariya Popova, Olexandr Isayev, Alexander Tropsha. Sci Adv 2018
202
37

Generative Recurrent Networks for De Novo Drug Design.
Anvita Gupta, Alex T Müller, Berend J H Huisman, Jens A Fuchs, Petra Schneider, Gisbert Schneider. Mol Inform 2018
112
30

Deep learning enables rapid identification of potent DDR1 kinase inhibitors.
Alex Zhavoronkov, Yan A Ivanenkov, Alex Aliper, Mark S Veselov, Vladimir A Aladinskiy, Anastasiya V Aladinskaya, Victor A Terentiev, Daniil A Polykovskiy, Maksim D Kuznetsov, Arip Asadulaev,[...]. Nat Biotechnol 2019
174
28

The rise of deep learning in drug discovery.
Hongming Chen, Ola Engkvist, Yinhai Wang, Marcus Olivecrona, Thomas Blaschke. Drug Discov Today 2018
351
25

Planning chemical syntheses with deep neural networks and symbolic AI.
Marwin H S Segler, Mike Preuss, Mark P Waller. Nature 2018
333
25

Long short-term memory.
S Hochreiter, J Schmidhuber. Neural Comput 1997
24

ZINC 15--Ligand Discovery for Everyone.
Teague Sterling, John J Irwin. J Chem Inf Model 2015
843
23

GuacaMol: Benchmarking Models for de Novo Molecular Design.
Nathan Brown, Marco Fiscato, Marwin H S Segler, Alain C Vaucher. J Chem Inf Model 2019
88
26


Extended-connectivity fingerprints.
David Rogers, Mathew Hahn. J Chem Inf Model 2010
22

Application of Generative Autoencoder in De Novo Molecular Design.
Thomas Blaschke, Marcus Olivecrona, Ola Engkvist, Jürgen Bajorath, Hongming Chen. Mol Inform 2018
110
21


Reinforced Adversarial Neural Computer for de Novo Molecular Design.
Evgeny Putin, Arip Asadulaev, Yan Ivanenkov, Vladimir Aladinskiy, Benjamin Sanchez-Lengeling, Alán Aspuru-Guzik, Alex Zhavoronkov. J Chem Inf Model 2018
87
22

Deep learning.
Yann LeCun, Yoshua Bengio, Geoffrey Hinton. Nature 2015
19


Applications of machine learning in drug discovery and development.
Jessica Vamathevan, Dominic Clark, Paul Czodrowski, Ian Dunham, Edgardo Ferran, George Lee, Bin Li, Anant Madabhushi, Parantu Shah, Michaela Spitzer,[...]. Nat Rev Drug Discov 2019
267
19

ChEMBL: a large-scale bioactivity database for drug discovery.
Anna Gaulton, Louisa J Bellis, A Patricia Bento, Jon Chambers, Mark Davies, Anne Hersey, Yvonne Light, Shaun McGlinchey, David Michalovich, Bissan Al-Lazikani,[...]. Nucleic Acids Res 2012
17

De Novo Design of Bioactive Small Molecules by Artificial Intelligence.
Daniel Merk, Lukas Friedrich, Francesca Grisoni, Gisbert Schneider. Mol Inform 2018
94
18

Enumeration of 166 billion organic small molecules in the chemical universe database GDB-17.
Lars Ruddigkeit, Ruud van Deursen, Lorenz C Blum, Jean-Louis Reymond. J Chem Inf Model 2012
325
16

The cornucopia of meaningful leads: Applying deep adversarial autoencoders for new molecule development in oncology.
Artur Kadurin, Alexander Aliper, Andrey Kazennov, Polina Mamoshina, Quentin Vanhaelen, Kuzma Khrabrov, Alex Zhavoronkov. Oncotarget 2017
86
18

Adversarial Threshold Neural Computer for Molecular de Novo Design.
Evgeny Putin, Arip Asadulaev, Quentin Vanhaelen, Yan Ivanenkov, Anastasia V Aladinskaya, Alex Aliper, Alex Zhavoronkov. Mol Pharm 2018
52
26

Concepts of Artificial Intelligence for Computer-Assisted Drug Discovery.
Xin Yang, Yifei Wang, Ryan Byrne, Gisbert Schneider, Shengyong Yang. Chem Rev 2019
110
14

A Deep Learning Approach to Antibiotic Discovery.
Jonathan M Stokes, Kevin Yang, Kyle Swanson, Wengong Jin, Andres Cubillos-Ruiz, Nina M Donghia, Craig R MacNair, Shawn French, Lindsey A Carfrae, Zohar Bloom-Ackermann,[...]. Cell 2020
211
14

Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models.
Daniil Polykovskiy, Alexander Zhebrak, Benjamin Sanchez-Lengeling, Sergey Golovanov, Oktai Tatanov, Stanislav Belyaev, Rauf Kurbanov, Aleksey Artamonov, Vladimir Aladinskiy, Mark Veselov,[...]. Front Pharmacol 2020
25
56

"Found in Translation": predicting outcomes of complex organic chemistry reactions using neural sequence-to-sequence models.
Philippe Schwaller, Théophile Gaudin, Dávid Lányi, Costas Bekas, Teodoro Laino. Chem Sci 2018
82
15

Molecular generative model based on conditional variational autoencoder for de novo molecular design.
Jaechang Lim, Seongok Ryu, Jin Woo Kim, Woo Youn Kim. J Cheminform 2018
53
24

ChemTS: an efficient python library for de novo molecular generation.
Xiufeng Yang, Jinzhe Zhang, Kazuki Yoshizoe, Kei Terayama, Koji Tsuda. Sci Technol Adv Mater 2017
48
27

Deep Reinforcement Learning for Multiparameter Optimization in de novo Drug Design.
Niclas Ståhl, Göran Falkman, Alexander Karlsson, Gunnar Mathiason, Jonas Boström. J Chem Inf Model 2019
34
38

De novo generation of hit-like molecules from gene expression signatures using artificial intelligence.
Oscar Méndez-Lucio, Benoit Baillif, Djork-Arné Clevert, David Rouquié, Joerg Wichard. Nat Commun 2020
47
27

The Synthesizability of Molecules Proposed by Generative Models.
Wenhao Gao, Connor W Coley. J Chem Inf Model 2020
34
38

Quantifying the chemical beauty of drugs.
G Richard Bickerton, Gaia V Paolini, Jérémy Besnard, Sorel Muresan, Andrew L Hopkins. Nat Chem 2012
402
13

MoleculeNet: a benchmark for molecular machine learning.
Zhenqin Wu, Bharath Ramsundar, Evan N Feinberg, Joseph Gomes, Caleb Geniesse, Aneesh S Pappu, Karl Leswing, Vijay Pande. Chem Sci 2017
316
12

Protein-Ligand Scoring with Convolutional Neural Networks.
Matthew Ragoza, Joshua Hochuli, Elisa Idrobo, Jocelyn Sunseri, David Ryan Koes. J Chem Inf Model 2017
215
12

QSAR modeling: where have you been? Where are you going to?
Artem Cherkasov, Eugene N Muratov, Denis Fourches, Alexandre Varnek, Igor I Baskin, Mark Cronin, John Dearden, Paola Gramatica, Yvonne C Martin, Roberto Todeschini,[...]. J Med Chem 2014
639
12

Entangled Conditional Adversarial Autoencoder for de Novo Drug Discovery.
Daniil Polykovskiy, Alexander Zhebrak, Dmitry Vetrov, Yan Ivanenkov, Vladimir Aladinskiy, Polina Mamoshina, Marine Bozdaganyan, Alexander Aliper, Alex Zhavoronkov, Artur Kadurin. Mol Pharm 2018
59
20

Machine learning in chemoinformatics and drug discovery.
Yu-Chen Lo, Stefano E Rensi, Wen Torng, Russ B Altman. Drug Discov Today 2018
221
12

PubChem Substance and Compound databases.
Sunghwan Kim, Paul A Thiessen, Evan E Bolton, Jie Chen, Gang Fu, Asta Gindulyte, Lianyi Han, Jane He, Siqian He, Benjamin A Shoemaker,[...]. Nucleic Acids Res 2016
12


Innovation in the pharmaceutical industry: New estimates of R&D costs.
Joseph A DiMasi, Henry G Grabowski, Ronald W Hansen. J Health Econ 2016
895
12

The ChEMBL database in 2017.
Anna Gaulton, Anne Hersey, Michał Nowotka, A Patrícia Bento, Jon Chambers, David Mendez, Prudence Mutowo, Francis Atkinson, Louisa J Bellis, Elena Cibrián-Uhalte,[...]. Nucleic Acids Res 2017
736
12

Molecular graph convolutions: moving beyond fingerprints.
Steven Kearnes, Kevin McCloskey, Marc Berndl, Vijay Pande, Patrick Riley. J Comput Aided Mol Des 2016
291
11

PubChem 2019 update: improved access to chemical data.
Sunghwan Kim, Jie Chen, Tiejun Cheng, Asta Gindulyte, Jia He, Siqian He, Qingliang Li, Benjamin A Shoemaker, Paul A Thiessen, Bo Yu,[...]. Nucleic Acids Res 2019
865
11

Boosting Docking-Based Virtual Screening with Deep Learning.
Janaina Cruz Pereira, Ernesto Raúl Caffarena, Cicero Nogueira Dos Santos. J Chem Inf Model 2016
109
11


Optimization of Molecules via Deep Reinforcement Learning.
Zhenpeng Zhou, Steven Kearnes, Li Li, Richard N Zare, Patrick Riley. Sci Rep 2019
54
20

Multi-objective de novo drug design with conditional graph generative model.
Yibo Li, Liangren Zhang, Zhenming Liu. J Cheminform 2018
55
20

Randomized SMILES strings improve the quality of molecular generative models.
Josep Arús-Pous, Simon Viet Johansson, Oleksii Prykhodko, Esben Jannik Bjerrum, Christian Tyrchan, Jean-Louis Reymond, Hongming Chen, Ola Engkvist. J Cheminform 2019
37
29

BindingDB in 2015: A public database for medicinal chemistry, computational chemistry and systems pharmacology.
Michael K Gilson, Tiqing Liu, Michael Baitaluk, George Nicola, Linda Hwang, Jenny Chong. Nucleic Acids Res 2016
378
10


Co-cited is the co-citation frequency, indicating how many articles cite the article together with the query article. Similarity is the co-citation as percentage of the times cited of the query article or the article in the search results, whichever is the lowest. These numbers are calculated for the last 100 citations when articles are cited more than 100 times.