Papers citing Self-referencing embedded strings (SELFIES): A 100% robust molecular string representation
Fragment-based Sequential Translation for Molecular Optimization
ChemRxiv · 2021
Benson Chen, Xiang Fu, Tommi Jaakkola, Regina Barzilay
Read original paper ↗ ·Fragment-based Sequential Translation for Molecular Optimization
ChemRxiv · 2021
Benson Chen, Xiang Fu, Regina Barzilay, Tommi Jaakkola
Read original paper ↗ ·Grand challenges on accelerating discovery in catalysis
Catalysis Today · 2021
Alessandra Toniato, Alain C. Vaucher, Teodoro Laino
Read original paper ↗ ·Goal-directed generation of new molecules by AI methods
Elsevier eBooks · 2021
Jules Leguy, Thomas Cauchy, Béatrice Duval, Benoit Da Mota
Read original paper ↗ ·Generative Deep Learning for Targeted Compound Design
Journal of Chemical Information and Modeling · 2021
T. Ferra de Sousa, João Vitor Mariano Correia, Vítor Pereira, Miguel Rocha
Read original paper ↗ ·De Novo Molecular Design with Chemical Language Models
Methods in molecular biology · 2021
Francesca Grisoni, Gisbert Schneider
Read original paper ↗ ·Deep Learning and Computational Chemistry
Methods in molecular biology · 2021
Tim James, Dimitar Hristozov
Read original paper ↗ ·Deep Learning Applied to Ligand-Based De Novo Drug Design
Methods in molecular biology · 2021
Ferruccio Palazzesi, Alfonso Pozzan
Read original paper ↗ ·Has Artificial Intelligence Impacted Drug Discovery?
Methods in molecular biology · 2021
Atanas Patronov, Kostas Papadopoulos, Ola Engkvist
Read original paper ↗ ·Predicting Antimicrobial Activity of Conjugated Oligoelectrolyte Molecules via Machine Learning
Journal of the American Chemical Society · 2021
Armi Tiihonen, Sarah J. Cox‐Vázquez, Qiaohao Liang, Mohamed Ragab, Zekun Ren, Noor Titan Putri Hartono, Zhe Liu, Shijing Sun, Cheng Yu Zhou, Nathan C. Incandela, Jakkarin Limwongyut, Alex S. Moreland, J. Senthilnath, Guillermo Carlos Bazan, Tonio Buonassisi
Read original paper ↗ ·Artificial Intelligence for Autonomous Molecular Design: A Perspective
Molecules · 2021
Rajendra Prasad Joshi, Neeraj Kumar
Read original paper ↗ ·Molecular generation by Fast Assembly of (Deep)SMILES fragments
Journal of Cheminformatics · 2021
Francois Berenger, Koji Tsuda
Read original paper ↗ ·Machine learning for polymeric materials: an introduction
Polymer International · 2021
Morgan M. Cencer, Jeffrey S. Moore, Rajeev S. Assary
Read original paper ↗ ·Active Site Sequence Representations of Human Kinases Outperform Full Sequence Representations for Affinity Prediction and Inhibitor Generation: 3D Effects in a 1D Model
Journal of Chemical Information and Modeling · 2021
Jannis Born, Tien Huynh, Astrid Stroobants, Wendy D. Cornell, Matteo Manica
Read original paper ↗ ·Using deep neural networks to explore chemical space
Expert Opinion on Drug Discovery · 2021
Martin Vogt
Read original paper ↗ ·ChemSpaX : exploration of chemical space by automated functionalization of molecular scaffold
Digital Discovery · 2022
Adarsh V. Kalikadien, Evgeny A. Pidko, Vivek Sinha
Read original paper ↗ ·Data storage architectures to accelerate chemical discovery: data accessibility for individual laboratories and the community
Chemical Science · 2022
Rebekah Duke, Vinayak Bhat, Chad M. Risko
Read original paper ↗ ·Image2SMILES: Transformer‐Based Molecular Optical Recognition Engine**
Chemistry - Methods · 2022
Ivan Khokhlov, Lev V. Krasnov, Maxim V. Fedorov, Sergey Sosnin
Read original paper ↗ ·Model agnostic generation of counterfactual explanations for molecules
Chemical Science · 2022
Geemi P. Wellawatte, Aditi Seshadri, Andrew Dickson White
Read original paper ↗ ·Molecular Sonification for Molecule to Music Information Transfer
Digital Discovery · 2022
Babak A. Mahjour, Jordan Bench, Rui Zhang, Jared Frazier, Tim Cernak
Read original paper ↗ ·Performance of chemical structure string representations for chemical image recognition using transformers
Digital Discovery · 2022
Kohulan Rajan, Christoph Steinbeck, Achim Zielesny
Read original paper ↗ ·Sigma profiles in deep learning: towards a universal molecular descriptor
Chemical Communications · 2022
Dinis O. Abranches, Yong Zhang, Edward Joseph Maginn, Yamil J. Colón
Read original paper ↗ ·From Platform to Knowledge Graph: Evolution of Laboratory Automation
JACS Au · 2022
Jiaru Bai, Liwei Cao, Sebastian Mosbach, Jethro Akroyd, Alexei A. Lapkin, Markus Kraft
Read original paper ↗ ·In silico design of microporous polymers for chemical separations and storage
Current Opinion in Chemical Engineering · 2022
Dylan M. Anstine, David S. Sholl, Joern Ilja Siepmann, Randall Q. Snurr, Alán Aspuru‐Guzik, Coray M. Colina
Read original paper ↗ ·Heterogeneous Catalysis in Grammar School
The Journal of Physical Chemistry C · 2022
Johannes T. Margraf, Zachary W. Ulissi, Yousung Jung, Karsten Reuter
Read original paper ↗ ·Analysis of Training and Seed Bias in Small Molecules Generated with a Conditional Graph-Based Variational Autoencoder─Insights for Practical AI-Driven Molecule Generation
Journal of Chemical Information and Modeling · 2022
Seung-Gu Kang, Joseph A. Morrone, Jeffrey K. Weber, Wendy D. Cornell
Read original paper ↗ ·A review of molecular representation in the age of machine learning
Wiley Interdisciplinary Reviews Computational Molecular Science · 2022
Daniel S. Wigh, Jonathan M. Goodman, Alexei A. Lapkin
Read original paper ↗ ·Scaffold-Retained Structure Generator to Exhaustively Create Molecules in an Arbitrary Chemical Space
Journal of Chemical Information and Modeling · 2022
Kazuma Kaitoh, Yoshihiro Yamanishi
Read original paper ↗ ·Molecular Design Learned from the Natural Product Porphyra-334: Molecular Generation via Chemical Variational Autoencoder versus Database Mining via Similarity Search, A Comparative Study
ACS Omega · 2022
Harada Yuki, Makoto Hatakeyama, Shuichi Maeda, Qi Gao, Kenichi Koizumi, Yuki Sakamoto, Yuuki Ono, Shinichiro Nakamura
Read original paper ↗ ·Molecular contrastive learning of representations via graph neural networks
Nature Machine Intelligence · 2022
Yuyang Wang, Jianren Wang, Zhonglin Cao, Amir Barati Farimani
Read original paper ↗ ·Genetic Optimization of Homogeneous Catalysts
Chemistry - Methods · 2022
Rubén Laplaza, Simone Gallarati, Clémence Corminbœuf
Read original paper ↗ ·Generative models for molecular discovery: Recent advances and challenges
Wiley Interdisciplinary Reviews Computational Molecular Science · 2022
Camille Bilodeau, Wengong Jin, Tommi Jaakkola, Regina Barzilay, Klavs F. Jensen
Read original paper ↗ ·Machine intelligence for chemical reaction space
Wiley Interdisciplinary Reviews Computational Molecular Science · 2022
Philippe Schwaller, Alain C. Vaucher, Rubén Laplaza, Charlotte Bunne, Andreas Krause, Clémence Corminbœuf, Teodoro Laino
Read original paper ↗ ·Unified Deep Learning Model for Multitask Reaction Predictions with Explanation
Journal of Chemical Information and Modeling · 2022
Jieyu Lü, Yingkai Zhang
Read original paper ↗ ·Pocket2Drug: An Encoder-Decoder Deep Neural Network for the Target-Based Drug Design
Frontiers in Pharmacology · 2022
Wentao Shi, Manali Singha, Gopal Narayan Srivastava, Limeng Pu, Jagannathan Ramanujam, Michał Bryliński
Read original paper ↗ ·Autonomous high-throughput computations in catalysis
Chem Catalysis · 2022
Stephan N. Steinmann, Angga Hermawan, Mohammed Bin Jassar, Zhi Wei Seh
Read original paper ↗ ·Recent advances and applications of deep learning methods in materials science
npj Computational Materials · 2022
Kamal Kumar Choudhary, Brian DeCost, Chi Chen, Anubhav Jain, Francesca Tavazza, Ryan Cohn, Cheol Woo Park, Alok Choudhary, Ankit Agrawal, Simon J. L. Billinge, Elizabeth A. Holm, Shyue Ping Ong, Chris M. Wolverton
Read original paper ↗ ·A graph neural network approach for molecule carcinogenicity prediction
Bioinformatics · 2022
Philip Fradkin, Adamo Young, Lazar Atanackovic, Brendan J. Frey, Leo J. Lee, Bo Wang
Read original paper ↗ ·Organic photoredox catalysts for CO2 reduction: Driving discovery with genetic algorithms
The Journal of Chemical Physics · 2022
Kareesa J. Kron, Andres Rodriguez-Katakura, Pranesh Regu, Maria N. Reed, Rachelle Elhessen, Shaama Mallikarjun Sharada
Read original paper ↗ ·Machine Learning Applications for Chemical Reactions
Chemistry - An Asian Journal · 2022
Sanggil Park, Herim Han, Hyungjun Kim, Sunghwan Choi
Read original paper ↗ ·Incorporating Target-Specific Pharmacophoric Information into Deep Generative Models for Fragment Elaboration
Journal of Chemical Information and Modeling · 2022
Thomas E. Hadfield, Fergus Imrie, Andy T. Merritt, Kristian Birchall, Charlotte Mary Deane
Read original paper ↗ ·In Silico Approaches for Addressing Challenges in CNS Radiopharmaceutical Design
ACS Chemical Neuroscience · 2022
Isaac M. Jackson, Eric Webb, Peter J. H. Scott, Michelle Louise James
Read original paper ↗ ·Challenges in Information-Mining the Materials Literature: A Case Study and Perspective
Chemistry of Materials · 2022
Andrew K. Smith, Vinayak Bhat, Qianxiang Ai, Chad M. Risko
Read original paper ↗ ·Approaches for enhancing the analysis of chemical space for drug discovery
Expert Opinion on Drug Discovery · 2022
Fernanda I. Saldívar‐González, José L. Medina‐Franco
Read original paper ↗ ·Language models can learn complex molecular distributions
Nature Communications · 2022
Daniel Flam-Shepherd, Kevin Zhu, Alán Aspuru‐Guzik
Read original paper ↗ ·Polygrammar: Grammar for Digital Polymer Representation and Generation
Advanced Science · 2022
Minghao Guo, Wan Shou, Liane Makatura, Timothy Erps, Michael Foshey, Wojciech Matusik
Read original paper ↗ ·Exploring Low-Toxicity Chemical Space with Deep Learning for Molecular Generation
Journal of Chemical Information and Modeling · 2022
Yuwei Yang, Zhenxing Wu, Xiaojun Yao, Yu Kang, Tingjun Hou, Chang‐Yu Hsieh, Huanxiang Liu
Read original paper ↗ ·Hydrogen storage metal-organic framework classification models based on crystal graph convolutional neural networks
Chemical Engineering Science · 2022
Xiuyang Lü, Zhizhong Xie, Xuanjun Wu, Mengmeng Li, Weiquan Cai
Read original paper ↗ ·Curiosity in exploring chemical spaces: intrinsic rewards for molecular reinforcement learning
Machine Learning Science and Technology · 2022
Luca Thiede, Mario Krenn, AkshatKumar Nigam, Alán Aspuru‐Guzik
Read original paper ↗ ·Bidirectional Graphormer for Reactivity Understanding: Neural Network Trained to Reaction Atom-to-Atom Mapping Task
Journal of Chemical Information and Modeling · 2022
Нугманов Рамиль Ирекович, Natalia Dyubankova, Andrey Gedich, Jörg K. Wegner
Read original paper ↗ ·