Convolutional embedding of attributed molecular graphs for physical property prediction

Coley, Connor W., Barzilay, Regina, Green, William H., Jaakkola, Tommi S., Jensen, Klavs F.·2017·Journal of Chemical Information and Modeling

Cited by (469)

Items 301–400 of 469

  1. TP-DDI: A Two-Pathway Deep Neural Network for Drug–Drug Interaction Prediction
    Jiang Xie, Chang Zhao, Jiaming Ouyang, Hongjian He, Dingkai Huang, Mengjiao Liu, Jiao Wang, Wenjun Zhang · 2022 · Interdisciplinary Sciences Computational Life Sciences
  2. Large variability and complexity of isothermal solubility for a series of redox-active phenothiazines
    Anton Sameera Perera, Thilini Malsha Suduwella, N. Harsha Attanayake, Rahul Kant Jha, William L. Eubanks, Ilya A. Shkrob, Chad M. Risko, Aman Preet Kaur, Susan A. Odom · 2022 · Materials Advances
  3. MLSolvA: solvation free energy prediction from pairwise atomistic interactions by machine learning
    Hyuntae Lim, YounJoon Jung · 2021 · Journal of Cheminformatics
  4. A deep learning method for predicting molecular properties and compound-protein interactions
    Jun Ma, Ruisheng Zhang, Tongfeng Li, Jing Jiang, Zhili Zhao, Yunwu Liu, Jun Ma · 2022 · Journal of Molecular Graphics and Modelling
  5. Analysis of uncertainty of neural fingerprint-based models
    Christian Feldmann, Jochen Sieg, Miriam Mathea · 2024 · Faraday Discussions
  6. GGAS2SN: Gated Graph and SmilesToSeq Network for Solubility Prediction
    Waqar Ahmad, Kil To Chong, Hilal Tayara · 2024 · Journal of Chemical Information and Modeling
  7. Hyper‐Mol: Molecular Representation Learning via Fingerprint‐Based Hypergraph
    Shicheng Cui, Qianmu Li, Deqiang Li, Zhichao Lian, Jun Hou · 2023 · Computational Intelligence and Neuroscience
  8. Grouping Matrix Based Graph Pooling with Adaptive Number of Clusters
    Sung Moon Ko, Sungjun Cho, Dae-Woong Jeong, Sehui Han, Moontae Lee, Honglak Lee · 2023 · Proceedings of the AAAI Conference on Artificial Intelligence
  9. Molecular sharing and molecular-specific representations for multimodal molecular property prediction
    Xuecong Tian, Sizhe Zhang, Ying Su, Wanhua Huang, Yongzheng Zhang, Xuan Ma, Keao Li, Xiaoyi Lv, Chen Chen, Cheng Chen · 2024 · Applied Soft Computing
  10. Multi-fidelity graph neural networks for predicting toluene/water partition coefficients
    Thomas Nevolianis, Jan G. Rittig, Alexander Mitsos, Kai O. Leonhard · 2025 · Journal of Cheminformatics
  11. Differential Compound Prioritization via Bidirectional Selectivity Push with Power
    Junfeng Liu, Xia Ning · 2017 · Journal of Chemical Information and Modeling
  12. Imbalanced Toxicity Prediction Using Multi-Task Learning and Over-Sampling
    Jincheng Li · 2020 · International Conference on Machine Learning and Cybernetics
  13. PluGeN: Multi-Label Conditional Generation from Pre-trained Models
    Maciej Wołczyk, Magdalena Proszewska, Łukasz Maziarka, Maciej Zięba, Patryk Wielopolski, Rafał Kurczab, Marek Śmieja · 2022 · Proceedings of the AAAI Conference on Artificial Intelligence
  14. The Unreasonable Effectiveness of Equations: Advanced Modeling For Biopharmaceutical Process Development
    Pablo A. Rolandi · 2019 · Computer-aided chemical engineering/Computer aided chemical engineering
  15. Do Large Scale Molecular Language Representations Capture Important Structural Information
    Jerret Ross, Brian M. Belgodere, Vijil Chenthamarakshan, Inkit Padhi, Youssef Mroueh, Payel Das · 2021 · arXiv (Cornell University)
  16. Holo-Mol: An explainable hybrid deep learning framework for predicting reactivity of hydroxyl radical to water contaminants based on holographic fused molecular representations
    Dianhui Mao, J Q Liu, Xuebo Li, Min Zuo, Wenjing Yan · 2024 · Chemical Engineering Journal
  17. Lightweight and high-precision materials property prediction using pre-trained Graph Neural Networks and its application to a small dataset
    Kento Nishio, Kiyou Shibata, Teruyasu Mizoguchi · 2024 · Applied Physics Express
  18. Molecular identification via molecular fingerprint extraction from atomic force microscopy images
    Manuel González Lastre, Pablo Pou, Miguel Wiche, Daniel Ebeling, André Schirmeisen, Rubén Pérez · 2024 · Journal of Cheminformatics
  19. Hierarchical Graph Attention Network with Positive and Negative Attentions for Improved Interpretability: ISA-PN
    Jinyong Park, Minhi Han, Kiwoong Lee, Sungnam Park · 2024 · Journal of Chemical Information and Modeling
  20. Predicting photodegradation rate constants of water pollutants on TiO2 using graph neural network and combined experimental-graph features
    Mahia V. Solout, Jahan Bakhsh Ghasemi · 2025 · Scientific Reports
  21. Molecular Representation Matters: Comparative Evaluation of Fingerprints, RDKit Descriptors, and Hashing Effects
    Shijia Zhou, Junqing Li, Ziyi Liu, Dongqi Wang · 2026 · The Journal of Physical Chemistry Letters
  22. Prediction Models for Fraction of Absorption and Membrane Permeability using Mordred Descriptors
    Tsuyoshi Esaki, Tomoki Yonezawa, Daisuke Yamazaki, Kazuyoshi Ikeda · 2022 · Chem-Bio Informatics Journal
  23. Structural and functional prediction, evaluation, and validation in the post-sequencing era
    Chang Li, Yixuan Luo, Yibo Xie, Zaifeng Zhang, Ye Liu, Lihui Zou, Fei Xiao · 2023 · Computational and Structural Biotechnology Journal
  24. A Hybrid GNN Approach for Improved Molecular Property Prediction
    Pedro Quesado, Luis H.M. Torres, Bernardete Ribeiro, Joel Perdiz Arrais · 2024 · Journal of Computational Biology
  25. Ultrahigh Throughput Protein–Ligand Docking with Deep Learning
    Austin Clyde · 2021 · Methods in molecular biology
  26. Predicting 2H NMR acyl chain order parameters with graph neural networks
    Markus Fischer, Benedikt Schwarze, Nikola Ristic, Holger A. Scheidt · 2022 · Computational Biology and Chemistry
  27. Automatic creation of molecular substructures for accurate estimation of pure component properties using connectivity matrices
    Qiong Pan, Xiaolei Fan, Jie Li · 2022 · Chemical Engineering Science
  28. Biomolecular Topology: Modelling and Analysis
    Jian Liu, Kelin Xia, Jie Wu, Stephen S.‐T. Yau, Guo‐Wei Wei · 2022 · Acta Mathematica Sinica English Series
  29. Evaluation of Methods for Protein Representation Learning: A Quantitative Analysis
    Serbülent Ünsal, Heval Ataş, Muammer Albayrak, Kemal Turhan, Aybar C. Acar, Tunca Doğan · 2020 · bioRxiv (Cold Spring Harbor Laboratory)
  30. Mechanism-Aware Deep Learning for Polar Reaction Prediction
    Ryan J. Miller, Alexander E. Dashuta, Brayden Rudisill, David L. Van Vranken, Pierre Baldi · 2025 · Journal of the American Chemical Society
  31. Interpretable and Physicochemical-Intuitive Deep Learning Approach for the Design of Thermal Resistance of Energetic Compounds
    Haitao Liu, Chen Peng, Chaoyang Zhang, Xin Huang · 2024 · The Journal of Physical Chemistry A
  32. Recent Development, Applications, and Patents of Artificial Intelligence in Drug Design and Development
    Prashant Kumar, Alpana Mahor, Roopam Tomar · 2025 · Current Drug Discovery Technologies
  33. Machine Learning in Drug Design
    Ola Engkvist, Lewis Mervin, Hongming Chen, Ting Ran · 2023 · Royal Society of Chemistry eBooks
  34. Evaluating Scalable Uncertainty Estimation Methods for DNN-Based Molecular Property Prediction
    Gabriele Scalia, Colin A. Grambow, Barbara Pernici, Yi‐Pei Li, William H. Green · 2019 · arXiv (Cornell University)
  35. Hybridization of SMILES and chemical-environment-aware tokens to improve performance of molecular structure generation
    Herim Han, Min Sun Yeom, Sunghwan Choi · 2025 · Scientific Reports
  36. Machine Learning‐Enabled Polymer Discovery for Enhanced Pulmonary siRNA Delivery
    Felix Sieber‐Schäfer, Min Jiang, Adrian P. E. Kromer, Anny Nguyen, Müge Molbay, Simone Pinto Carneiro, David C. Jürgens, Gerald Burgstaller, Bastian Popper, Benjamin Winkeljann et al. · 2025 · Advanced Functional Materials
  37. Screening of potential candidates for solid electrolyte interphase materials for lithium-ion batteries through a data-driven approach
    Sadhana Barman, Utpal Sarkar · 2025 · Physical Chemistry Chemical Physics
  38. Molecular machine learning in chemical process design
    Jan G. Rittig, Manuel Dahmen, Martin Grohe, Philippe Schwaller, Alexander Mitsos · 2026 · Current Opinion in Chemical Engineering
  39. Generative AI in Drug Designing: Current State-of-the-Art and Perspectives
    Shaban Ahmad, Nagmi Bano, Sakshi Sharma, Shafiya Sakina, Naeem Ahmad, Khalid Raza · 2024 · Studies in computational intelligence
  40. An Effective Pipeline for Training Variational Autoencoders for Synthesizable and Optimized Molecular Design
    Fardeen H. Mozumder, Byung-Jun Yoon · 2024 · IEEE Access
  41. Online OCHEM multi-task model for solubility and lipophilicity prediction of platinum complexes
    Nesma Mousa, Hristo P. Varbanov, Vidya Kaipanchery, Elisabetta Gabano, Mauro Ravera, Andrey Andreevich Toropov, Larisa Charochkina, Filipe Menezes, Guillaume Godin, Igor V. Tetko · 2025 · Journal of Inorganic Biochemistry
  42. Improved graph‐based multitask learning model with sparse sharing for quantitative structure–property relationship prediction of drug molecules
    Haoyang Hu, Yun‐Ke Bai, Zhihong Yuan · 2022 · AIChE Journal
  43. InteractionNet: Modeling and Explaining of Noncovalent Protein-Ligand Interactions with Noncovalent Graph Neural Network and Layer-Wise Relevance Propagation
    Hyeoncheol Cho, Eok Kyun Lee, Insung S. Choi · 2020 · arXiv (Cornell University)
  44. Quantum Topological Atomic Properties of 44K molecules
    Brandon Meza-González, David Ignacio Ramírez‐Palma, Pablo Carpio‐Martínez, David Vázquez-Cuevas, Karina Martínez‐Mayorga, Fernando Cortés‐Guzmán · 2024 · Scientific Data
  45. MAPCliff-WMGR: Exploring Activity Cliffs in Molecular Activity Prediction Enhanced by Weighted Molecular Graph Representations
    Yiwei Chen, Tingfang Wu, Yelu Jiang, Liangpeng Nie, Geng Li, Yi Zhang, Zhenglong Zhou, Jia Xu, Lijun Quan, Qiang Lyu · 2025 · Journal of Chemical Information and Modeling
  46. Quantitatively determining melting properties for energetic compounds via knowledge-infused molecular graphs and interpretable deep learning
    Peng Chen, Haitao Liu, Chaoyang Zhang, Xin Huang · 2024 · Energetic Materials Frontiers
  47. MultiGraph Attention Network for analyzing Company Relations
    Natraj Raman, Grace Bang, Azadeh Nematzadeh · 2019 · International Conference on Computing and Pattern Recognition (ICCPR)
  48. Substitutional alloying using crystal graph neural networks
    Dario Massa, Daniel Cieśliński, Amirhossein D. Naghdi, Stefanos Papanikolaou · 2024 · AIP Advances
  49. MultiChem: predicting chemical properties using multi-view graph attention network
    Heesang Moon, Mina Rho · 2025 · BioData Mining
  50. Effects of Pooling Operations on Prediction of Ligand Rotation‐Dependent Protein–Ligand Binding in 3D Graph Convolutional Network
    Yeji Kim, Jihoo Kim, Won June Kim, Eok Kyun Lee, Insung S. Choi · 2021 · Bulletin of the Korean Chemical Society
  51. Calculation of Protein-Ligand Binding Free Energy Using a Physics-Guided Neural Network
    Sahar Cain, Ali Risheh, Negin Forouzesh · 2021 · IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
  52. Deep Learning Based-Virtual Screening Using 2D Pharmacophore Fingerprint in Drug Discovery
    Seloua Hadiby, Yamina Mohamed Ben Ali · 2022 · Neural Processing Letters
  53. Geometric machine learning: research and applications
    Wenming Cao, Canta Zheng, Zhiyue Yan, Zhihai He, Weixin Xie · 2022 · Multimedia Tools and Applications
  54. Towards explainable message passing networks for predicting carbon dioxide adsorption in metal-organic frameworks
    Ali Raza, Faaiq Waqar, Árni Sturluson, Cory M. Simon, Xiaoli Z. Fern · 2020 · arXiv (Cornell University)
  55. Building Attention and Edge Convolution Neural Networks for Bioactivity and Physical-Chemical Property Prediction
    Michael Withnall, Edvard Lindelöf, Ola Engkvist, Hongming Chen · 2019 · ChemRxiv
  56. Stereoelectronics-Aware Molecular Representation Learning
    Daniil A. Boiko, Thiago Reschützegger, Benjamín Sánchez-Lengeling, Samuel M. Blau, Gabe Gomes · 2022 · ChemRxiv
  57. WITHDRAWN
    Jun Xia, Lecheng Zhang, Xiao Zhu, Stan Ziqing Li · 2023 · ChemRxiv
  58. CSstep: Step-by-step exploration of the chemical space of drug molecules via multi-agent and multi-stage reinforcement learning
    Xinhao Che, Yujing Zhao, Qilei Liu, Fang Yu, Hanyu Gao, Lei Zhang · 2025 · Chemical Engineering Science
  59. Hierarchical attention graph learning with LLM enhancement for molecular solubility prediction
    Yangxin Fan, Yinghui Wu, Roger H. French, Danny Pérez, Michael G. Taylor, Ping Xiong Yang · 2025 · Digital Discovery
  60. Gram matrix: an efficient representation of molecular conformation and learning objective for molecular pretraining
    Wenkai Xiang, Feisheng Zhong, Lin Ni, Mingyue Zheng, Xutong Li, Qian Shi, Dingyan Wang · 2024 · Briefings in Bioinformatics
  61. Can graph similarity metrics be helpful for analogue identification as part of a read-across approach?
    Brett Hagan, Imran Shah, Grace Y. Patlewicz · 2025 · Computational Toxicology
  62. FanNet: A mesh convolution operator for learning dense maps
    Güneş Sucu, Sinan Kalkan, Yusuf Sahillioğlu · 2025 · Computers & Graphics
  63. Automation of some macromolecular properties using a machine learning approach
    Merjem Hoxha, Hiqmet Kamberaj · 2021 · Machine Learning Science and Technology
  64. Ageing and Alzheimer’s Disease
    Ruixue Ai, Xurui Jin, Bowen Tang, Guang Yang, Zhangming Niu, Evandro Fei Fang · 2021 · Springer eBooks
  65. BERT-based drug structure presentation: A comparison of tokenizers
    Давронов Рифкат Раxимович, Адилова Фатима Туичиевна · 2023 · AIP conference proceedings
  66. Advancement of Computational Design Drug Delivery System in COVID- 19: Current Updates and Future Crosstalk- A Critical Update
    A. K.M. Mohiuddin, Sumanta Mondal · 2023 · Infectious Disorders - Drug Targets
  67. The a priori screening of potential organic solvents using artificial neural networks
    Nivaar Brijmohan, Kuveneshan Moodley, Caleb Narasigadu · 2023 · Fluid Phase Equilibria
  68. Construction of a multi-tissue compound–target interaction network of Qingfei Paidu decoction in COVID-19 treatment based on deep learning and transcriptomic analysis
    Xia Li, Xuetong Zhao, Xinjian Yu, Jianping Zhao, Xiangdong Fang · 2024 · Journal of Bioinformatics and Computational Biology
  69. Interpretable Drug Response Prediction through Molecule Structure-aware and Knowledge-Guided Visible Neural Network
    Jiancong Xie, Zhe Zhang, Youyou Li, Jiahua Rao, Yuedong Yang · 2024 · IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
  70. Tutorial
    Cao Xiao, Jimeng Sun · 2019 · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)
  71. Feature Selection on Imbalanced Data and Its Application on Toxicity Prediction
    Jincheng Li · 2020 · International Conference on Machine Learning and Cybernetics
  72. Poisson kernel: Avoiding self-smoothing in graph convolutional networks
    Ziqing Yang, Shoudong Han, Jun Zhao · 2021 · Pattern Recognition
  73. On The Interpretability of Graph Neural Networks in QSPR Modeling
    Fan Fan, Adem R.N. Aouichaoui, Gürkan Sin · 2022 · Computer-aided chemical engineering/Computer aided chemical engineering
  74. An In-depth Summary of Recent Artificial Intelligence Applications in Drug Design
    Zhang, Yi · 2021 · arXiv (Cornell University)
  75. Bridging functional annotation gaps in non-model plant genes with AlphaFold, DeepFRI and small molecule docking
    Georgie Stephan, Benjamin Dugdale, Pradeep Chand Deo, Robert M. Harding, James Langham Dale, Paul Visendi · 2021 · bioRxiv (Cold Spring Harbor Laboratory)
  76. TeachOpenCADD goes Deep Learning: Open-source Teaching Platform Exploring Molecular DL Applications
    Michael Backenköhler, Paula Linh Kramer, Joschka Groß, Gerrit Großmann, Roman Joeres, Azat Tagirdzhanov, Dominique Sydow, Hamza Ibrahim, Floriane Odje, Verena Wolf et al. · 2023 · ChemRxiv
  77. Why Deep Models Often Cannot Beat Non-deep Counterparts on Molecular Property Prediction?
    Jun Xia, Lecheng Zhang, Xiao Zhu, Stan Ziqing Li · 2023 · ChemRxiv
  78. SMILES-X: autonomous molecular compounds characterization for small datasets without descriptors
    G. Lambard, Ekaterina Gracheva · 2020 · Machine Learning Science and Technology
  79. Molecular fingerprints: application and techniques
    Konrad Witkowski, Agnieszka Duraj, Piotr S. Szczepaniak · 2024 · Procedia Computer Science
  80. SynthMol: A Drug Safety Prediction Framework Integrating Graph Attention and Molecular Descriptors into Pre-Trained Geometric Models
    Zidong Su, Rong Zhang, Xiaoyu Fan, Boxue Tian · 2025 · Journal of Chemical Information and Modeling
  81. QSAR and Machine Learning Predictors
    Philipe Oliveira Fernandes, Vinícius Gonçalves Maltarollo · 2024 · Computer-aided drug discovery and design
  82. Machine Learning Accelerated Analysis of Chemical Reaction Networks for Gas-Phase Reaction Systems
    Yan Liu, Yiming Mo, Youwei Cheng · 2025 · Industrial & Engineering Chemistry Research
  83. Knowledge graph information bottleneck enhanced molecular representation learning
    Jiaxin Dai, Dongmei Fu, Zhongwei Qiu, Lingwei Ma, Dawei Zhang · 2025 · Neural Networks
  84. Learning Hierarchical Representations for Explainable Chemical Reaction Prediction
    Jingyi Hou, Zhen Dong · 2023 · Applied Sciences
  85. Graph machine learning in drug discovery
    Mohit Pandey, Atia Hamidizadeh, Mariia Radaeva, Michael Fernández, Martin Ester, Artem R Cherkasov · 2023 · Elsevier eBooks
  86. ACR-GNN: Adaptive Cluster Reinforcement Graph Neural Network Based on Contrastive Learning
    Jianpeng Hu, Shengfu Ning, Meng Yan, Yifan Cao, Zhishen Nie, Ying Lin · 2023 · Neural Processing Letters
  87. Toward a comprehensive understanding of alicyclic compounds: Bio-effects perspective and deep learning approach
    Wenjie Shi, Kunsen Lin, Youcai Zhao, Zongsheng Li, Tao Zhou · 2023 · The Science of The Total Environment
  88. Many-body expansion based machine learning models for octahedral transition metal complexes
    Ralf Meyer, Daniel B. K. Chu, Heather J. Kulik · 2024 · Machine Learning Science and Technology
  89. A Two-Stage End-to-End Deep Learning Approach for Predicting Astrochemical Reactions
    Jiawei Wang, Yanan Zhang, Haili Bu, Lü Yang, Manni Duan, Donghui Quan, Peng Qiu · 2025 · Intelligent Computing
  90. Ensemble Geometric Deep Learning of Aqueous Solubility
    Mohammad Mehdi Ghahremanpour, Anastasia Saar, Julian Tirado‐Rives, William L. Jorgensen · 2023 · Journal of Chemical Information and Modeling
  91. Calculation of protein-ligand binding entropies using a rule-based molecular fingerprint
    Ali Risheh, Alles Rebel, Paul S. Nerenberg, Negin Forouzesh · 2024 · Biophysical Journal
  92. Learning Strategic Network Emergence Games
    Rakshit Trivedi, Hongyuan Zha B · 2020 · neural information processing systems
  93. Prediction of Bioconcentration Factors (BCF) using Graph Neural Networks
    Edgar Iván Sánchez Medina, Steffen Linke, Kai Sundmacher · 2021 · Computer-aided chemical engineering/Computer aided chemical engineering
  94. CRNNTL: convolutional recurrent neural network and transfer learning for QSAR modelling
    Yaqin Li, Yongjin Xu, Yi Yu · 2021 · arXiv (Cornell University)
  95. Prediction of Carbon Nanostructure Mechanical Properties and Role of Defects Using Machine Learning
    Qi Zhao, Jordan J. Winetrout, Yanxun Xu, Yusu Wang, Hendrik Heinz · 2021 · arXiv (Cornell University)
  96. Graph neural networks for the prediction of molecular structure-property relationships
    Jan G. Rittig, Qinghe Gao, Manuel Dahmen, Alexander Mitsos, Artur M. Schweidtmann · 2022 · arXiv (Cornell University)
  97. WITHDRAWN
    Jun Xia, Lecheng Zhang, Xiao Zhu, Stan Ziqing Li · 2023 · ChemRxiv
  98. Predicting aqueous and organic solubilities with machine learning: a workflow for identifying organic co-solvents
    Maurycy Krzyżanowski, Sirazam Munira Aishee, Nirala Singh, Bryan R. Goldsmith · 2025 · ChemRxiv
  99. A drug molecular classification model based on graph structure generation
    Lixuan Che, Yide Jin, Yuliang Shi, Xiaojing Yu, Hongfeng Sun, Hui Liu, Xinyu Li · 2023 · Journal of Biomedical Informatics
  100. Predicting the Binding of Small Molecules to Proteins through Invariant Representation of the Molecular Structure
    Roberta Beccaria, Andrea Lazzeri, Guido Tiana · 2024 · Journal of Chemical Information and Modeling