Papers citing Self-referencing embedded strings (SELFIES): A 100% robust molecular string representation
Evolutionary Multi-objective Design of SARS-CoV-2 Protease Inhibitor Candidates
Lecture notes in computer science · 2020
Tim Cofala, Lars Elend, Philip Mirbach, Jonas Prellberg, Thomas Teusch, Oliver Kramer
Read original paper ↗ ·A Deep-Learning View of Chemical Space Designed to Facilitate Drug Discovery
Journal of Chemical Information and Modeling · 2020
Paul Maragakis, Hunter M. Nisonoff, Brian Cole, David Elliot Shaw
Read original paper ↗ ·VAE-Sim: A Novel Molecular Similarity Measure Based on a Variational Autoencoder
Molecules · 2020
Soumitra Samanta, Steve O’Hagan, Neil Swainston, Timothy J. Roberts, Douglas Bruce Kell
Read original paper ↗ ·Applications of machine learning in metal-organic frameworks
Coordination Chemistry Reviews · 2020
Sanggyu Chong, Sangwon Lee, Baekjun Kim, Jihan Kim
Read original paper ↗ ·Graph Neural Networks for Prediction of Fuel Ignition Quality
Energy & Fuels · 2020
Artur M. Schweidtmann, Jan G. Rittig, Andrea Anna König, Martin Grohe, Alexander Mitsos, Manuel Dahmen
Read original paper ↗ ·Designing and understanding light-harvesting devices with machine learning
Nature Communications · 2020
Florian Häse, Loı̈c M. Roch, Pascal Friederich, Alán Aspuru‐Guzik
Read original paper ↗ ·EvoMol: a flexible and interpretable evolutionary algorithm for unbiased de novo molecular generation
Journal of Cheminformatics · 2020
Jules Leguy, Thomas Cauchy, Marta Glavatskikh, Béatrice Duval, Benoit Da Mota
Read original paper ↗ ·OptiMol : Optimization of Binding Affinities in Chemical Space for Drug Discovery
Journal of Chemical Information and Modeling · 2020
Jacques Boitreaud, Vincent Mallet, Carlos Oliver, Jérôme Waldispühl
Read original paper ↗ ·DECIMER: towards deep learning for chemical image recognition
Journal of Cheminformatics · 2020
Kohulan Rajan, Achim Zielesny, Christoph Steinbeck
Read original paper ↗ ·Mining Heterogeneous Data for Formulation Design
IEEE ... International Conference on Data Mining workshops · 2020
Krati Saxena, Ashwini B. Patil, Sagar Sunkle, Vinay Kulkarni
Read original paper ↗ ·Assessing methods and obstacles in chemical space exploration
Applied AI Letters · 2020
Shawn Reeves, Benjamin R. DiFrancesco, Vijay M. Shahani, Stephen Scott MacKinnon, Andreas Windemuth, Andrew E. Brereton
Read original paper ↗ ·Machine Learning for Electronically Excited States of Molecules
Chemical Reviews · 2020
Julia Westermayr, Philipp Marquetand
Read original paper ↗ ·Deep learning and generative methods in cheminformatics and chemical biology: navigating small molecule space intelligently
Biochemical Journal · 2020
Douglas Bruce Kell, Soumitra Samanta, Neil Swainston
Read original paper ↗ ·Reusability report: Designing organic photoelectronic molecules with descriptor conditional recurrent neural networks
Nature Machine Intelligence · 2020
Somesh Mohapatra, Tzuhsiung Yang, Rafael Gómez‐Bombarelli
Read original paper ↗ ·Polymers for Extreme Conditions Designed Using Syntax-Directed Variational Autoencoders
Chemistry of Materials · 2020
Rohit Batra, Hanjun Dai, Tran Doan Huan, Lihua Chen, Chiho Kim, Will R. Gutekunst, Le Song, Rampi Ramprasad
Read original paper ↗ ·Digitizing Chemistry Using the Chemical Processing Unit: From Synthesis to Discovery
Accounts of Chemical Research · 2020
Liam Wilbraham, S. Hessam M. Mehr, Leroy Cronin
Read original paper ↗ ·Data-driven algorithms for inverse design of polymers
Soft Matter · 2021
Kianoosh Sattari, Yunchao Xie, Jian Lin
Read original paper ↗ ·Exploring Local Chemical Space in De Novo Molecular Generation Using Multi-Agent Deep Reinforcement Learning
Natural Science · 2021
Wei Hu
Read original paper ↗ ·Inverse Molecule Design with Invertible Neural Networks as Generative Models
Journal of Biomedical Science and Engineering · 2021
Wei Hu
Read original paper ↗ ·Machine learning, artificial intelligence, and data science breaking into drug design and neglected diseases
Wiley Interdisciplinary Reviews Computational Molecular Science · 2021
José Peña Guerrero, Paul Nguewa, Alfonso T. García‐Sosa
Read original paper ↗ ·Inverse design of nanoporous crystalline reticular materials with deep generative models
Nature Machine Intelligence · 2021
Zhenpeng Yao, Benjamín Sánchez-Lengeling, N. Scott Bobbitt, Benjamin J. Bucior, Sai Govind Hari Kumar, Sean P. Collins, Thomas D. Burns, Tom K. Woo, Omar K. Farha, Randall Q. Snurr, Alán Aspuru‐Guzik
Read original paper ↗ ·Navigating through the Maze of Homogeneous Catalyst Design with Machine Learning
Trends in Chemistry · 2021
Gabe Gomes, Robert Pollice, Alán Aspuru‐Guzik
Read original paper ↗ ·Data-Driven Strategies for Accelerated Materials Design
Accounts of Chemical Research · 2021
Robert Pollice, Gabe Gomes, Matteo Aldeghi, Riley J. Hickman, Mario Krenn, Cyrille Lavigne, Michael Lindner-D’Addario, AkshatKumar Nigam, Cher Tian Ser, Zhenpeng Yao, Alán Aspuru‐Guzik
Read original paper ↗ ·Data Science in Chemical Engineering: Applications to Molecular Science
Annual Review of Chemical and Biomolecular Engineering · 2021
Chowdhury M. Ashraf, Nisarg Joshi, David A. C. Beck, Jim Pfaendtner
Read original paper ↗ ·SMILES Pair Encoding: A Data-Driven Substructure Tokenization Algorithm for Deep Learning
Journal of Chemical Information and Modeling · 2021
Xinhao Li, Denis Fourches
Read original paper ↗ ·Deep Learning Optical Spectroscopy Based on Experimental Database: Potential Applications to Molecular Design
JACS Au · 2021
Joonyoung F. Joung, Minhi Han, Jinhyo Hwang, Minseok Jeong, Dong Hoon Choi, Sungnam Park
Read original paper ↗ ·Automation and computer-assisted planning for chemical synthesis
Nature Reviews Methods Primers · 2021
Yuning Shen, Julia E. Borowski, Melissa A. Hardy, Richmond Sarpong, Abigail G. Doyle, Tim Cernak
Read original paper ↗ ·STOUT: SMILES to IUPAC names using neural machine translation
Journal of Cheminformatics · 2021
Kohulan Rajan, Achim Zielesny, Christoph Steinbeck
Read original paper ↗ ·Current and future deep learning algorithms for tandem mass spectrometry (MS/MS)‐based small molecule structure elucidation
Rapid Communications in Mass Spectrometry · 2021
Youzhong Liu, Thomas De Vijlder, Wout Bittremieux, Kris Laukens, Wouter Heyndrickx
Read original paper ↗ ·Comparison of structure- and ligand-based scoring functions for deep generative models: a GPCR case study
Journal of Cheminformatics · 2021
Morgan C. Thomas, Robert T. Smith, Noel M. O’Boyle, Chris de Graaf, Andreas Bender
Read original paper ↗ ·Machine learning directed drug formulation development
Advanced Drug Delivery Reviews · 2021
Pauric Bannigan, Matteo Aldeghi, Zeqing Bao, Florian Häse, Alán Aspuru‐Guzik, Christine J. Allen
Read original paper ↗ ·Masked graph modeling for molecule generation
Nature Communications · 2021
Omar Mahmood, Elman Mansimov, Richard Bonneau, Kyunghyun Cho
Read original paper ↗ ·Materials representation and transfer learning for multi-property prediction
Applied Physics Reviews · 2021
Shufeng Kong, Dan Guevarra, Carla Pedro Gomes, John M. Gregoire
Read original paper ↗ ·Adsorption Enthalpies for Catalysis Modeling through Machine-Learned Descriptors
Accounts of Chemical Research · 2021
Mie Andersen, Karsten Reuter
Read original paper ↗ ·Paradigm Shift: The Promise of Deep Learning in Molecular Systems Engineering and Design
Frontiers in Chemical Engineering · 2021
Abdulelah S. Alshehri, Fengqi You
Read original paper ↗ ·Deep molecular dreaming: inverse machine learning for de-novo molecular design and interpretability with surjective representations
Machine Learning Science and Technology · 2021
Cynthia Shen, Mario Krenn, Sagi Eppel, Alán Aspuru‐Guzik
Read original paper ↗ ·Assigning confidence to molecular property prediction
Expert Opinion on Drug Discovery · 2021
AkshatKumar Nigam, Robert Pollice, Matthew F. D. Hurley, Riley J. Hickman, Matteo Aldeghi, Naruki Yoshikawa, Seyone Chithrananda, Vincent A. Voelz, Alán Aspuru‐Guzik
Read original paper ↗ ·Deep learning for predictions of hydrolysis rates and conditional molecular design of esters
Journal of the Taiwan Institute of Chemical Engineers · 2021
Po-Hao Chiu, Yan-Lin Yang, Heng‐Kwong Tsao, Yu‐Jane Sheng
Read original paper ↗ ·Chemical language models enable navigation in sparsely populated chemical space
Nature Machine Intelligence · 2021
Michael A. Skinnider, Richard Greg Stacey, David Scott Wishart, Leonard J. Foster
Read original paper ↗ ·Machine Learning in Chemical Engineering: Strengths, Weaknesses, Opportunities, and Threats
Engineering · 2021
Maarten R. Dobbelaere, Pieter P. Plehiers, Ruben Van de Vijver, Christian Victor Stevens, Kevin M. Van Geem
Read original paper ↗ ·Bi-modal Variational Autoencoders for Metabolite Identification Using Tandem Mass Spectrometry
bioRxiv (Cold Spring Harbor Laboratory) · 2021
Svetlana Kutuzova, Christian Igel, Mads Eggert Nielsen, Douglas McCloskey
Read original paper ↗ ·Ab Initio Machine Learning in Chemical Compound Space
Chemical Reviews · 2021
Bing Huang, O. Anatole von Lilienfeld
Read original paper ↗ ·A Gentle Introduction to Graph Neural Networks
Distill · 2021
Benjamín Sánchez-Lengeling, Emily Reif, Adam Pearce, Alexander B. Wiltschko
Read original paper ↗ ·DECIMER 1.0: deep learning for chemical image recognition using transformers
Journal of Cheminformatics · 2021
Kohulan Rajan, Achim Zielesny, Christoph Steinbeck
Read original paper ↗ ·Chemputation and the Standardization of Chemical Informatics
JACS Au · 2021
Alexander J. S. Hammer, Artem I. Leonov, Nicola L. Bell, Leroy Cronin
Read original paper ↗ ·Molecular Generators and Optimizers Failure Modes
Malaysian Journal of Medical and Biological Research · 2021
Mani Manavalan
Read original paper ↗ ·Applied Machine Learning for Developing Next‐Generation Functional Materials
Advanced Functional Materials · 2021
Filip Dinic, Kamalpreet Singh, Tony Dong, Milad Rezazadeh, Zhibo Wang, Ali Khosrozadeh, Tiange Yuan, Oleksandr Voznyy
Read original paper ↗ ·TRIOMPHE: Transcriptome-Based Inference and Generation of Molecules with Desired Phenotypes by Machine Learning
Journal of Chemical Information and Modeling · 2021
Kazuma Kaitoh, Yoshihiro Yamanishi
Read original paper ↗ ·Machine learning for next-generation nanotechnology in healthcare
Matter · 2021
Andżelika Lorenc, Bárbara B. Mendes, João Conniot, Diana P. Sousa, João Conde, Tiago Rodrigues
Read original paper ↗ ·Translating the InChI: adapting neural machine translation to predict IUPAC names from a chemical identifier
Journal of Cheminformatics · 2021
Jennifer Handsel, Brian Matthews, Nicola Knight, Simon John Coles
Read original paper ↗ ·