Papers citing Self-referencing embedded strings (SELFIES): A 100% robust molecular string representation
Molecular represention in AI-assisted synthesis chemistry: from sequence to graph
Scientia Sinica Chimica · 2022
Hongshuai Wang, Lujie Jin, Jie Feng, Zhihao Dong, Wei Deng, Youyong Li
Read original paper ↗ ·Ab initio machine learning of phase space averages
The Journal of Chemical Physics · 2022
Jan Weinreich, Dominik Lemm, Guido Falk von Rudorff, O. Anatole von Lilienfeld
Read original paper ↗ ·Testing the Limits of SMILES-based De Novo Molecular Generation with Curriculum and Deep Reinforcement Learning
bioRxiv (Cold Spring Harbor Laboratory) · 2022
Maranga Mokaya, Fergus Imrie, Willem P. van Hoorn, Aleksandra Kalisz, Anthony R Bradley, Charlotte Mary Deane
Read original paper ↗ ·Stereoelectronics-Aware Molecular Representation Learning
ChemRxiv · 2022
Daniil A. Boiko, Thiago Reschützegger, Benjamín Sánchez-Lengeling, Samuel M. Blau, Gabe Gomes
Read original paper ↗ ·MACAW: An Accessible Tool for Molecular Embedding and Inverse Molecular Design
Journal of Chemical Information and Modeling · 2022
Vincent Blay, Tijana Radivojević, Jonathan Allen, Corey M Hudson, Héctor García Martín
Read original paper ↗ ·Deep Learning Concepts and Applications for Synthetic Biology
GEN Biotechnology · 2022
William Beardall, Guy-Bart V. Stan, Mary J. Dunlop
Read original paper ↗ ·Chemoton 2.0: Autonomous Exploration of Chemical Reaction Networks
Journal of Chemical Theory and Computation · 2022
Jan P. Unsleber, Stephanie A. Grimmel, Markus Reiher
Read original paper ↗ ·Multi-objective goal-directed optimization of de novo stable organic radicals for aqueous redox flow batteries
Nature Machine Intelligence · 2022
Shree Sowndarya S. V., Jeffrey Law, Charles Edison Tripp, Dmitry Duplyakin, Erotokritos Skordilis, David Biagioni, Robert S. Paton, Peter C. St. John
Read original paper ↗ ·MICER: a pre-trained encoder–decoder architecture for molecular image captioning
Bioinformatics · 2022
Jiacai Yi, Chengkun Wu, Xiaochen Zhang, Xinyi Xiao, Yanlong Qiu, Wentao Zhao, Tingjun Hou, Dongsheng Cao
Read original paper ↗ ·VLA-SMILES: Variable-Length-Array SMILES Descriptors in Neural Network-Based QSAR Modeling
Machine Learning and Knowledge Extraction · 2022
Antonina L. Nazarova, Aiichiro Nakano
Read original paper ↗ ·ChemicalX: A Deep Learning Library for Drug Pair Scoring
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · 2022
Benedek Rózemberczki, Charles Tapley Hoyt, Anna A. Gogleva, Piotr Grabowski, Klas Karis, Andrej Lamov, Andriy Nikolov, Sebastian Nilsson, Michaël Ughetto, Yu Wang, Tyler Derr, Benjamin M. Gyori
Read original paper ↗ ·DDIPred: Graph Convolutional Network-Based Drug-drug Interactions Prediction Using Drug Chemical Structure Embedding
IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB) · 2022
Shaghayegh Sadeghi, Alioune Ngom
Read original paper ↗ ·Human- and machine-centred designs of molecules and materials for sustainability and decarbonization
Nature Reviews Materials · 2022
Jiayu Peng, Daniel Schwalbe‐Koda, Karthik Akkiraju, Tian Xie, Livia Giordano, Yang Yu, C. John Eom, Jaclyn R. Lunger, Daniel J. Zheng, Reshma R. Rao, Sokseiha Muy, Jeffrey C. Grossman, Karsten Reuter, Rafael Gómez‐Bombarelli, Yang Shao‐Horn
Read original paper ↗ ·SMICLR: Contrastive Learning on Multiple Molecular Representations for Semisupervised and Unsupervised Representation Learning
Journal of Chemical Information and Modeling · 2022
Gabriel A. Pinheiro, Juarez L. F. Da Silva, Marcos G. Quiles
Read original paper ↗ ·When machine learning meets molecular synthesis
Trends in Chemistry · 2022
João C. A. Oliveira, Johanna Frey, Shuo‐Qing Zhang, Li‐Cheng Xu, Xin Li, Shuwen Li, Xin Hong, Lutz Ackermann
Read original paper ↗ ·Review of techniques and models used in optical chemical structure recognition in images and scanned documents
Journal of Cheminformatics · 2022
Fidan Musazade, Narmin Jamalova, Jamaladdin Hasanov
Read original paper ↗ ·On the value of popular crystallographic databases for machine learning prediction of space groups
Acta Materialia · 2022
Vishwesh Venkatraman, P.A. Carvalho
Read original paper ↗ ·Deep learning methods for molecular representation and property prediction
Drug Discovery Today · 2022
Zhen Li, Mingjian Jiang, Shuang Wang, Shugang Zhang
Read original paper ↗ ·TUCAN: A molecular identifier and descriptor applicable to the whole periodic table from hydrogen to oganesson
Journal of Cheminformatics · 2022
Jan C. Brammer, Gerd Blanke, Claudia Kellner, Alexander Hoffmann, Sonja Herres‐Pawlis, Ulrich Schatzschneider
Read original paper ↗ ·ParticleGrid: Enabling Deep Learning using 3D Representation of Materials
IEEE International Conference on eScience · 2022
Shehtab Zaman, Ethan Ferguson, Cécile Pereira, Denis Akhivarov, Mauricio Araya‐Polo, Kenneth Chiu
Read original paper ↗ ·Roles and opportunities for machine learning in organic molecular crystal structure prediction and its applications
MRS Bulletin · 2022
Rebecca J. Clements, Joshua Dickman, Jay Johal, Jennie Martin, Joseph Glover, Graeme Matthew Day
Read original paper ↗ ·SELFIES and the future of molecular string representations
Patterns · 2022
Mario Krenn, Qianxiang Ai, Senja Barthel, Nessa Carson, Angelo Frei, Nathan C. Frey, Pascal Friederich, Théophile Gaudin, Alberto Alexander Gayle, Kevin Maik Jablonka, Rafael F. Lameiro, Dominik Lemm, Alston Lo, Seyed Mohamad Moosavi, José Manuel Nápoles-Duarte, AkshatKumar Nigam, Robert Pollice, Kohulan Rajan, Ulrich Schatzschneider, Philippe Schwaller, Marta Skreta, Berend Smit, Felix Strieth‐Kalthoff, Chong Sun, Gary Tom, Guido Falk von Rudorff, Andrew Wang, Andrew Dickson White, Adamo Young, Rose Yu, Alán Aspuru‐Guzik
Read original paper ↗ ·Training recurrent neural networks as generative neural networks for molecular structures: how does it impact drug discovery?
Expert Opinion on Drug Discovery · 2022
Sofia D’Souza, K. V. Prema, S. Balaji
Read original paper ↗ ·Bridging Chemical Knowledge and Machine Learning for Performance Prediction of Organic Synthesis
Chemistry - A European Journal · 2022
Shuo‐Qing Zhang, Li‐Cheng Xu, Shu‐Wen Li, João C. A. Oliveira, Xin Li, Lutz Ackermann, Xin Hong
Read original paper ↗ ·Chemical transformer compression for accelerating both training and inference of molecular modeling
Machine Learning Science and Technology · 2022
Yi Yu, Karl Börjesson
Read original paper ↗ ·Operationally meaningful representations of physical systems in neural networks
Machine Learning Science and Technology · 2022
Hendrik Poulsen Nautrup, Tony Metger, Raban Iten, Sofiène Jerbi, Lea M. Trenkwalder, Henrik Wilming, Hans J. Briegel, Renato Renner
Read original paper ↗ ·Text‐based representations with interpretable machine learning reveal structure–property relationships of polybenzenoid hydrocarbons
Journal of Physical Organic Chemistry · 2022
Shachar Fite, Alexandra Wahab, Eno Paenurk, Zeev Gross, Renana Gershoni‐Poranne
Read original paper ↗ ·Machine learning for a sustainable energy future
Nature Reviews Materials · 2022
Zhenpeng Yao, Yanwei Lum, Andrew K. Johnston, L.M. Mejía-Mendoza, Xin Zhou, Yonggang Wen, Alán Aspuru‐Guzik, Edward Hartley Sargent, Zhi Wei Seh
Read original paper ↗ ·Optimizing interactions to protein binding sites by integrating docking-scoring strategies into generative AI methods
Frontiers in Chemistry · 2022
Susanne Sauer, Hans Matter, Gerhard Heßler, Christoph Grebner
Read original paper ↗ ·ICAN: Interpretable cross-attention network for identifying drug and target protein interactions
PLoS ONE · 2022
Hiroyuki Kurata, Sho Tsukiyama
Read original paper ↗ ·An Artificial Intelligence Framework for Optimal Drug Design
bioRxiv (Cold Spring Harbor Laboratory) · 2022
Grace D. Ramey, Santiago Vargas, Dinesh P. de Alwis, Anastassia N. Alexandrova, Joe Distefano, Peter Bloomingdale
Read original paper ↗ ·CAT: A Compound Attachment Tool for the Construction of Composite Chemical Compounds
Journal of Chemical Information and Modeling · 2022
Bas van Beek, Juliette Zito, Lucas Visscher, Ivan Infante
Read original paper ↗ ·Inverse QSAR: Reversing Descriptor-Driven Prediction Pipeline Using Attention-Based Conditional Variational Autoencoder
Journal of Chemical Information and Modeling · 2022
William Bort, Daniyar Mazitov, Dragos Horvath, Fanny Bonachéra, Arkadii Lin, Gilles Marcou, Igor I. Baskin, Timur Madzhidov, Alexandre A. Varnek
Read original paper ↗ ·Learning to discover medicines
International Journal of Data Science and Analytics · 2022
Minh-Tri Nguyen, Thin Nguyen, Truyen Tran
Read original paper ↗ ·Improved graph‐based multitask learning model with sparse sharing for quantitative structure–property relationship prediction of drug molecules
AIChE Journal · 2022
Haoyang Hu, Yun‐Ke Bai, Zhihong Yuan
Read original paper ↗ ·Graph machine learning for design of high‐octane fuels
AIChE Journal · 2022
Jan G. Rittig, Martin Ritzert, Artur M. Schweidtmann, Stefanie Winkler, Jana M. Weber, Philipp Morsch, Karl Alexander Heufer, Martin Grohe, Alexander Mitsos, Manuel Dahmen
Read original paper ↗ ·The impact of low-cost molecular geometry optimization in property prediction via graph neural network
IEEE International Conference on Machine Learning and Applications (ICMLA) · 2022
Gabriel A. Pinheiro, Felipe V. Calderan, Juarez L. F. Da Silva, Marcos G. Quiles
Read original paper ↗ ·Docking-based Multi-objective Molecular optimization Pipeline using Structure-constrained Genetic Algorithm
IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · 2022
Yurim Lee, Kyudam Choi, Cheongwon Kim
Read original paper ↗ ·HierMRL: Hierarchical Structure-Aware Molecular Representation Learning for Property Prediction
IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · 2022
Maotao Liu, Yifan Yang, Xu Gong, Li Liu, Qun Liu
Read original paper ↗ ·How machine learning can accelerate electrocatalysis discovery and optimization
Materials Horizons · 2022
Stephan N. Steinmann, Qing Wang, Zhi Wei Seh
Read original paper ↗ ·Application of Machine Learning to the Design of Energetic Materials: Preliminary Experience and Comparison with Alternative Techniques
Propellants Explosives Pyrotechnics · 2022
Clément Wespiser, Didier Mathieu
Read original paper ↗ ·PanGu Drug Model: learn a molecule like a human
Science China Life Sciences · 2022
Xinyuan Lin, Chi Xu, Zhaoping Xiong, Xinfeng Zhang, Ningxi Ni, Bolin Ni, Jianlong Chang, Ruiqing Pan, Zidong Wang, Fan Yu, Qi Chuan Tian, Hualiang Jiang, Mingyue Zheng, Nan Qiao
Read original paper ↗ ·Large-scale chemical language representations capture molecular structure and properties
Nature Machine Intelligence · 2022
Jerret Ross, Brian M. Belgodere, Vijil Chenthamarakshan, Inkit Padhi, Youssef Mroueh, Payel Das
Read original paper ↗ ·Advances in deep learning-based 3D molecular generative models
Scientia Sinica Chimica · 2022
Shaolun Yao, Jie Song, Zunlei Feng, Lingxiang Jia, Zipeng Zhong, Mingli Song
Read original paper ↗ ·Critical Assessment of Generative Models for de Novo Molecular Structure Generation
Journal of Computer Aided Chemistry · 2023
Tomoyuki Miyao
Read original paper ↗ ·Data-driven discovery of innate immunomodulators via machine learning-guided high throughput screening
Chemical Science · 2023
Yifeng Tang, Jeremiah Y. Kim, Carman KM IP, Azadeh Bahmani, Qing Chen, Matthew Glenn Rosenberger, Aaron Palmer Esser-Kahn, Andrew L. Ferguson
Read original paper ↗ ·Deep learning methodologies in drug design
Elsevier eBooks · 2023
Haralambos Sarimveis, Chrysoula Gousiadou, Philip Doganis, Pantelis Karatzas, Iason Sotiropoulos, Periklis Tsiros
Read original paper ↗ ·Graph Neural Networks for Molecules
Challenges and advances in computational chemistry and physics · 2023
Yuyang Wang, Zijie Li, Amir Barati Farimani
Read original paper ↗ ·Machine learning methods in photochemistry and photophysics
Elsevier eBooks · 2023
Jingbai Li, Morgane Vacher, Pavlo O. Dral, Steven A. Lopez
Read original paper ↗ ·Recent advances in deep learning enabled approaches for identification of molecules of therapeutics relevance
Elsevier eBooks · 2023
Kushagra Kashyap, Mohammad Imran Siddiqi
Read original paper ↗ ·