Deep Reinforcement Learning for De-Novo Drug Design

29 November 2017

Papers citing "Deep Reinforcement Learning for De-Novo Drug Design"

50 / 200 papers shown

Title
Inverse Design of Potential Singlet Fission Molecules using a Transfer Learning Based Approach Akshay Subramanian Utkarsh Saha Tejasvini Sharma N. Tailor S. Satapathi 14 1 0 17 Mar 2020
Reinforcement Learning for Molecular Design Guided by Quantum Mechanics G. Simm Robert Pinsler José Miguel Hernández-Lobato AI4CE 21 82 0 18 Feb 2020
Improving Molecular Design by Stochastic Iterative Target Augmentation Kevin Kaichuang Yang Wengong Jin Kyle Swanson Regina Barzilay Tommi Jaakkola 30 26 0 11 Feb 2020
Exploring Chemical Space using Natural Language Processing Methodologies for Drug Discovery Hakime Öztürk Arzucan Özgür P. Schwaller Teodoro Laino Elif Özkirimli 27 116 0 10 Feb 2020
Multi-Objective Molecule Generation using Interpretable Substructures Wengong Jin Regina Barzilay Tommi Jaakkola 19 23 0 08 Feb 2020
Hierarchical Generation of Molecular Graphs using Structural Motifs Wengong Jin Regina Barzilay Tommi Jaakkola 21 279 0 08 Feb 2020
Big-Data Science in Porous Materials: Materials Genomics and Machine Learning Kevin Maik Jablonka D. Ongari S. M. Moosavi B. Smit AI4CE 31 350 0 18 Jan 2020
Black Box Recursive Translations for Molecular Optimization Farhan N. Damani Vishnu Sresht Stephen Ra 22 5 0 21 Dec 2019
A Deep Reinforcement Learning Architecture for Multi-stage Optimal Control Yuguang Yang 9 1 0 25 Nov 2019
CORE: Automatic Molecule Optimization Using Copy & Refine Strategy Tianfan Fu Cao Xiao Jimeng Sun 31 63 0 23 Nov 2019
Molecular Generative Model Based On Adversarially Regularized Autoencoder S. Hong Jaechang Lim Seongok Ryu W. Kim GAN DRL GNN 31 63 0 13 Nov 2019
Machine learning for molecular simulation Frank Noé A. Tkatchenko K. Müller C. Clementi AI4CE 12 642 0 07 Nov 2019
Multiple-objective Reinforcement Learning for Inverse Design and Identification Haoran Wei Mariefel V. Olarte Garrett B. Goh AI4CE 16 3 0 09 Oct 2019
Generating valid Euclidean distance matrices Moritz Hoffmann Frank Noé 21 56 0 07 Oct 2019
Learning Everywhere: A Taxonomy for the Integration of Machine Learning and Simulations Geoffrey C. Fox S. Jha AI4CE 24 13 0 29 Sep 2019
Synthetic Data for Deep Learning Sergey I. Nikolenko 46 348 0 25 Sep 2019
GEN: Highly Efficient SMILES Explorer Using Autodidactic Generative Examination Networks R. V. Deursen P. Ertl Igor V. Tetko Guillaume Godin 11 32 0 10 Sep 2019
Regression-clustering for Improved Accuracy and Training Cost with Molecular-Orbital-Based Machine Learning Lixue Cheng Nikola B. Kovachki Matthew Welborn Thomas F. Miller 20 44 0 04 Sep 2019
$PaccMann$^{RL}$: Designing anticancer drugs from transcriptomic data via reinforcement learning$ PaccMann $^{RL}$ : Designing anticancer drugs from transcriptomic data via reinforcement learning Jannis Born Matteo Manica Ali Oskooei Joris Cadow Karsten Borgwardt María Rodríguez Martínez 27 0 0 29 Aug 2019
Reinforcement Learning in Healthcare: A Survey Chao Yu Jiming Liu S. Nemati LM&MA OffRL 19 549 0 22 Aug 2019
ChemBO: Bayesian Optimization of Small Organic Molecules with Synthesizable Recommendations Ksenia Korovina Sailun Xu Kirthevasan Kandasamy W. Neiswanger Barnabás Póczós J. Schneider Eric P. Xing 31 121 0 05 Aug 2019
Generative Models for Automatic Chemical Design Daniel Schwalbe-Koda Rafael Gómez-Bombarelli MedIm AI4CE 32 81 0 02 Jul 2019
Efficient Navigation of Colloidal Robots in an Unknown Environment via Deep Reinforcement Learning Yuguang Yang M. Bevan Bo Li 6 0 0 26 Jun 2019
Deep Reinforcement Learning for Cyber Security Thanh Thi Nguyen Vijay Janapa Reddi OffRL AI4CE 10 313 0 13 Jun 2019
Hierarchical Graph-to-Graph Translation for Molecules Wengong Jin Regina Barzilay Tommi Jaakkola 26 16 0 11 Jun 2019
Probabilistic hypergraph grammars for efficient molecular optimization E. Kraev Mark Harley 16 1 0 05 Jun 2019
Symmetry-adapted generation of 3d point sets for the targeted discovery of molecules Niklas W. A. Gebauer M. Gastegger Kristof T. Schütt 35 201 0 02 Jun 2019
Self-Referencing Embedded Strings (SELFIES): A 100% robust molecular string representation Mario Krenn Florian Hase AkshatKumar Nigam Pascal Friederich Alán Aspuru-Guzik 11 70 0 31 May 2019
Scaffold-based molecular design using graph generative model Jaechang Lim Sang-Yeon Hwang Seungsu Kim Seokhyun Moon Woo Youn Kim 25 17 0 31 May 2019
MolecularRNN: Generating realistic molecular graphs with optimized properties Mariya Popova Mykhailo Shvets Junier Oliva Olexandr Isayev GNN 35 164 0 31 May 2019
All SMILES Variational Autoencoder Zaccary Alperstein Artem Cherkasov J. Rolfe DRL 14 38 0 30 May 2019
Adversarial Learned Molecular Graph Inference and Generation Sebastian Polsterl Christian Wachinger GAN 28 7 0 24 May 2019
Towards Explainable Anticancer Compound Sensitivity Prediction via Multimodal Attention-based Convolutional Encoders Matteo Manica Ali Oskooei Jannis Born Vigneshwar Subramanian J. Sáez-Rodríguez María Rodríguez Martínez 22 115 0 25 Apr 2019
Optimizing thermodynamic trajectories using evolutionary and gradient-based reinforcement learning Chris Beeler U. Yahorau Rory Coles Kyle Mills S. Whitelam Isaac Tamblyn 6 7 0 20 Mar 2019
Deep learning for molecular design - a review of the state of the art Daniel C. Elton Zois Boukouvalas M. Fuge Peter W. Chung AI4CE 3DV 24 326 0 11 Mar 2019
Deep learning in bioinformatics: introduction, application, and perspective in big data era Yu Li Chao Huang Lizhong Ding Zhongxiao Li Yijie Pan Xin Gao AI4CE 21 295 0 28 Feb 2019
Atomistic structure learning M. Jørgensen H. L. Mortensen S. A. Meldgaard E. L. Kolsbjerg Thomas L. Jacobsen K. H. Sørensen B. Hammer AI4CE 13 36 0 27 Feb 2019
Mol-CycleGAN - a generative model for molecular optimization Łukasz Maziarka Agnieszka Pocha Jan Kaczmarczyk Krzysztof Rataj M. Warchoł 20 241 0 06 Feb 2019
A Universal Density Matrix Functional from Molecular Orbital-Based Machine Learning: Transferability across Organic Molecules Lixue Cheng Matthew Welborn Anders S. Christensen Thomas F. Miller 22 93 0 10 Jan 2019
Learning Multimodal Graph-to-Graph Translation for Molecular Optimization Wengong Jin Kevin Kaichuang Yang Regina Barzilay Tommi Jaakkola 33 224 0 03 Dec 2018
Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models Daniil Polykovskiy Alexander Zhebrak Benjamín Sánchez-Lengeling Sergey Golovanov Oktai Tatanov ... Simon Johansson Hongming Chen Sergey I. Nikolenko Alán Aspuru-Guzik Alex Zhavoronkov ELM 197 633 0 29 Nov 2018
GuacaMol: Benchmarking Models for De Novo Molecular Design Nathan Brown Marco Fiscato Marwin H. S. Segler Alain C. Vaucher ELM 44 691 0 22 Nov 2018
Molecular Transformer - A Model for Uncertainty-Calibrated Chemical Reaction Prediction P. Schwaller Teodoro Laino John McGuinness A. Horváth Constantine Bekas A. Lee 25 719 0 06 Nov 2018
Generating equilibrium molecules with deep neural networks Niklas W. A. Gebauer M. Gastegger Kristof T. Schütt BDL 17 38 0 26 Oct 2018
Optimization of Molecules via Deep Reinforcement Learning Zhenpeng Zhou S. Kearnes Li Li R. Zare Patrick F. Riley AI4CE 21 532 0 19 Oct 2018
Deep Reinforcement Learning Yuxi Li VLM OffRL 28 144 0 15 Oct 2018
Conditional molecular design with deep generative models Seokho Kang Kyunghyun Cho BDL 172 183 0 30 Apr 2018
Fréchet ChemNet Distance: A metric for generative models for molecules in drug discovery Kristina Preuer Philipp Renz Thomas Unterthiner Sepp Hochreiter G. Klambauer MedIm 26 324 0 26 Mar 2018
Multi-Objective De Novo Drug Design with Conditional Graph Generative Model Yibo Li L. Zhang Zhenming Liu 35 335 0 18 Jan 2018
In silico generation of novel, drug-like chemical matter using the LSTM neural network P. Ertl Richard A. Lewis E. Martin V. Polyakov 17 59 0 20 Dec 2017