A graph-convolutional neural network model for the prediction of chemical reactivity

Cited by (679)

Items 601–679 of 679

1. Martensite Variant Identification For Shape Memory Alloys By Using Graph Neural Networks
   Yi-Ming Tseng, Pei-Te Wang, Nan-Yow Chen, An-Cheng Yang, Nien‐Ti Tsou · 2021 · Research Square
2. Reproducing the Invention of a Named Reaction: Predicting Unseen Chemical Reactions via Zero-Shot Learning
   An Su, Ling Wang, Xinqiao Wang, Chengyun Zhang, Hongliang Duan · 2021 · ChemRxiv
3. Uwb-GCN: Accelerating Graph Convolutional Networks Through Runtime Workload Rebalancing
   Tong Geng, Ang Li, Tianqi Wang, Chunshu Wu, Yanfei Li, Antonino Tumeo, Shuai Che, Steve Reinhardt, Martin Herbordt · 2021 · viXra
4. Molecular structure prediction based on graph convolutional networks.
   Xiaohui S. Lin, Yongquan Jiang, Yan T. Yang · 2021 · arXiv (Cornell University)
5. The Power of Computational Intelligence Methods in the Containment of COVID-19 Pandemic from Detection to Recovery
   Abdullahi Isa, Barka Piyinkir Ndahi · 2021 · IntechOpen eBooks
6. The Role of Big Data Analytics in Drug Discovery and Vaccine Development Against COVID-19
   2022 · Advances in data mining and database management book series
7. Automatic discovery of chemical reactions using imposed activation
   Cyrille Lavigne, Gabe Gomes, Robert Pollice, Alán Aspuru‐Guzik · 2020 · ChemRxiv
8. GraphRXN: A Novel Representation for Reaction Prediction
   Baiqing Li, Shimin Su, Chan Zhu, Jie Lin, Xinyue Hu, Lebin Su, Zhunzhun Yu, Kuangbiao Liao, Hongming Chen · 2022 · Research Square
9. Computer-Aided Synthesis Planning for Biocatalysis
   William Finnigan · 2023 · Elsevier eBooks
10. Bayesian optimisation for additive screening and yieldimprovements in chemical reactions – beyond one-hot encoding
    Bojana Ranković, Ryan‐Rhys Griffiths, Henry B. Moss, Philippe Schwaller · 2023 · ChemRxiv
11. Connectivity Matrix-based Descriptors with Deep Learning for Estimation of Pure Component Properties
    Qiong Pan, Xiaolei Fan, Jie Li · 2023 · Computer-aided chemical engineering/Computer aided chemical engineering
12. Training Topology With Graph Neural Cellular Automata
    Daniel Dwyer, Maxwell M. Omwenga · 2023 · IEEE International Conference on Electro Information Technology
13. ORDerly: Datasets and benchmarks for chemical reaction data
    Daniel S. Wigh, Joe Arrowsmith, Alexander Pomberger, Kobi Felton, Alexei A. Lapkin · 2023 · ChemRxiv
14. A formula calculation model of multi-additive special coating based on K nearest neighbor algorithm
    Linghong Chi, jun Huang · 2023 · International Conference on Computer Information Science and Application Technology (CISAT)
15. Machine learning in reaction engineering
    Hanyu Gao · 2024 · Elsevier eBooks
16. Predicting Chemical Reaction Product by Graph Transformer
    Shunya Makino, Nobuaki Yasuo, Masakazu Sekijima · 2023 · Congress in Computer Science, Computer Engineering, and Applied Computing (CSCE)
17. A Crystal Knowledge-Enhanced Pre-training Framework for Crystal Property Estimation
    Haomin Yu, Yanru Song, Jilin Hu, Chenjuan Guo, Bin Yang, Christian S. Jensen · 2024 · Lecture notes in computer science
18. AI in Predictive Toxicology
    P. Selvakumar, A. Nandhakumar, M. Vignesh, K. Arun Patrick, J. Banupriya · 2024 · Advances in medical technologies and clinical practice book series
19. Synergistic Modeling of Liquid Properties: Integrating Neural Network-Derived Molecular Features with Modified Kernel Models
    Hyuntae Lim, YounJoon Jung · 2024 · Journal of Chemical Theory and Computation
20. MLCD: Machine Learning-Based Code Version and Device Selection for Heterogeneous Systems
    Kaiwen Cao, Hanchen Ye, Yihan Pang, Deming Chen · 2025 · IEEE Transactions on Computers
21. Enhancing Metabolomics Pathway Prediction with Sequential Graph Convolutional Network
    Bineesh Moozhippurath, N. Jayapandian · 2025 · IEEE International Conference on Communication Systems and Network Technologies (CSNT)
22. Peer Collaboration in DBLP Using Graph Convolutional Network
    Showkat Ahmad Dar · 2025 · SSRN Electronic Journal
23. From Code to Cure: How Generative AI Is Reinventing Drug Discovery
    Anil Kumar Shukla · 2025 · Research Square
24. Exploring the molecular potential of natural products against COVID-19 through molecular modeling and machine learning
    Rafael Vieira, Vitor Hugo Batista, Kally Alves de Sousa · 2025 · Next research.
25. Construction of Training Datasets for Chemical Reactivity Prediction Through Computational Means
    Thijs Stuyver, Javier Emilio Alfonso Ramos · 2025 · Wiley eBooks
26. Optimization of Catalysts Using Computational Chemistry, Machine Learning, and Cheminformatics
    David Dalmau, Juan V. Alegre‐Requena · 2025 · Wiley eBooks
27. Chemoenzymatic synthesis planning guided by synthetic potential scores
    Xuan Liu, Hongxiang Li, Huimin Zhao · 2025 · Digital Discovery
28. PTML models of self assembled ligand free nanoparticle catalysts for cross coupling reactions
    Andrea Ruiz-Escudero, Zuriñe Serna-Burgos, Sonia Arrasate, Humberto González‐Díaz · 2025 · Scientific Reports
29. Fluoride Electrolyte Discovery via Reactivity Guided Genetic Algorithms
    Vignesh Sathyaseelan, Brett Matthew Savoie · 2026 · The Journal of Physical Chemistry B
30. Oxidation states in solids from data-driven paradigms
    Yue Yin, Hai Yan Xiao · 2025 · Chemical Science
31. Sculpting the future: harnessing artificial intelligence for revolutionary drug discovery
    Antonio Lavecchia · 2025 · Elsevier eBooks
32. MAD-HiSpMV: Matrix Adaptive Design with Hybrid Row Distribution for Imbalanced SpMV Acceleration on FPGAs
    Manoj Bheemasandra Rajashekar, Akhil Raj Baranwal, Xingyu Tian, Zhenman Fang · 2025 · ACM Transactions on Reconfigurable Technology and Systems
33. Contrastive prior enhances the performance of Bayesian neural network-based molecular property prediction
    Chaoyu Wen, Chunyan Li, Jin Li · 2025 · Expert Systems with Applications
34. AI-Driven Drug Discovery: Leveraging Machine Learning for Predictive Molecular Design and Accelerated Pharmaceutical Innovation
    Ravikanth Konda, SingasaniTejesh Reddy, Shaik Ali Moon, Vishvanatha Raju, Rakesh Kumar, Siva koteswararao Katta · 2025 · IEEE World Conference on Applied Intelligence and Computing (AIC)
35. A Novel AI Framework for Accelerating Carbon Capture Solvent Discovery
    Davide Garbelotto, A. Lobo, U. Awasthi, O. Medvedev, S. Mukherjee, A. Aristov, Konstantin Polunin, Alex De Mur, Жуков Леонид Евгеньевич, A. Huseynov · 2025 · Abu Dhabi International Petroleum Exhibition & Conference (ADIPEC)
36. StraGCN: GPU-Accelerated Strassen’s Sparse-Dense Matrix Multiplication for Graph Convolutional Network Training
    Weidong He, Haikun Liu, Zhuohui Duan, Xiaofei Liao, Shuhao Zhang, Fubing Mao, Hai Jin · 2025 · International Conference for High Performance Computing, Networking, Storage and Analysis (SC)
37. Bond-editing driven electron flow mapping for reaction mechanism modeling
    Pengyu Liang, Bo Liu, Ruiqiang Lu, Jing Li, Yi Tan, Huanxiang Liu, Xiaojun Yao · 2025 · Chinese Chemical Letters
38. NCIVISION: A Siamese Neural Network for Molecular Similarity Prediction MEP and RDG Images
    Rafael Campos Vieira, Letícia de A. Nascimento, Arthur Alves Nascimento, NATHALIA CRISTINA CASTILHO ALVES, Érica C. M. Nascimento, João B. L. Martins · 2025 · Molecules
39. Guiding Evolutionary Molecular Design: Adding Reinforcement Learning for Mutation Selection
    Gaëlle Milon-Harnois, Chaïmaâ Touhami, Nicolas Gutowski, Benoit Da Mota, Thomas Cauchy · 2025 · IEEE International Conference on Tools with Artificial Intelligence (ICTAI)
40. Additional file 2 of A deep learning framework for accurate reaction prediction and its application on high-throughput experimentation data
    Li, Baiqing, Shimin Su, Chan Zhu, Lin, Jie, Hu, Xinyue, Lebin Su, Zhunzhun Yu, Kuangbiao Liao, Chen, Hongming · 2024 · Figshare
41. Additional file 1 of A deep learning framework for accurate reaction prediction and its application on high-throughput experimentation data
    Li, Baiqing, Shimin Su, Chan Zhu, Lin, Jie, Hu, Xinyue, Lebin Su, Zhunzhun Yu, Kuangbiao Liao, Chen, Hongming · 2024 · Figshare
42. Additional file 1 of In silico prediction of UGT-mediated metabolism in drug-like molecules via graph neural network
    Huang, Mengting, Chaofeng Lou, Wu, Zengrui, Li, Weihua, Philip W. Lee, Tang, Yun, Liu, Guixia · 2022 · Figshare
43. Additional file 1 of From theory to experiment: transformer-based generation enables rapid discovery of novel reactions
    Wang, Xinqiao, Yao, Chuansheng, Yun Zhang, Jiahui Yu, Haoran Qiao, Chengyun Zhang, Yejian Wu, Bai, Renren, Duan, Hongliang · 2022 · Figshare
44. Additional file 1 of AutoTemplate: enhancing chemical reaction datasets for machine learning applications in organic chemistry
    Chen, Lung-Yi, Yi‐Pei Li · 2024 · Figshare
45. RAKAN: An efficient residual-connected graph neural network for predicting molecular potential energy based on attention mechanism and Kolmogorov-Arnold
    Yanchun Yang, Zhengxing Huang, Ruijie Li, Qihui Rao, Jianchen Liu · 2025 · Chinese Journal of Chemical Physics
46. SymChemAI: A Symbolically Informed Neural Network for Physicochemical Modeling of Reaction Systems
    Souad Tayane, Jaafar Gaber · 2025 · E3S Web of Conferences
47. Prediction of Drug Metabolites
    Honglin Li, Shiliang Li · 2025 · Springer eBooks
48. AI in Retrosynthesis: Introduction, Methods, Evaluation, and Future Directions
    Ruchi Bharti, Ajay Thakur, Uma Koul, Monika Verma, Renu Sharma · 2026 · Springer eBooks
49. Multimodal Quantum Vision Transformer for Enzyme Commission Classification from Biochemical Representations
    Murat Isik, Mandeep Kaur Saggi, Humaira Gowher, Sabre Kais · 2025 · IEEE International Conference on Quantum Artificial Intelligence (QAI)
50. EnzRetro: Enzymatic Retrosynthetic Planning With Site‐Specific Reaction Edits Based on Sequence Generative Architecture
    Yahui Cao, Haoshu Chen, Tao Zhang, Xinyu Zhao, Bingzhi Li, Xiangrui Zheng · 2026 · Exploration
51. ABANet: An Atom-Bond Attention-Enhanced Neural Network for End-to-End Retrosynthesis
    Qing-Xiao Wang, Lei Chen, Xue-Ling Zhang, Xiaoxin Li · 2026 · Machine Learning
52. HerbGNN: A Directed Message Passing Neural Network Benchmark for Early Enrichment in Herbicide Virtual Screening under Extreme Class Imbalance
    Tonatiu Campos-García, Juan Vazquez-Martínez, Huitziméngari Campos · 2026 · Research Square
53. CHIMERA: A Multi-Level Representation Framework for Predicting Asymmetric Catalytic Reactions
    Zongyong Hu, Jiebin Su, Jiaxing Liu, Chunjin Wei, Cheng Wang, Da Zhou · 2026 · SSRN Electronic Journal
54. Weakly Supervised Segmentation and Context-Aware Classification in Computational Pathology
    Marvin Lerousseau · 2022 · theses.fr (ABES)
55. Modelling of transport properties of molecular ions of helium in air
    Martin Beseda · 2022
56. Astrochemical reaction networks : bringing order to chaos
    Lorenzo Tinacci · 2023
57. Predicting enzyme-compound associations for enzyme-catalysed reactions
    Liam Brydon, Gillian Dobbie, Katerina Taškova, Jörg Simon Wicker · 2026 · Journal of Cheminformatics
58. Weighted Views Representation with Multi-Head Coulomb Attention for Molecular Property Prediction
    Muhammad Shahzeb Ali, Martin J. Mohlenkamp · 2026 · ACS Omega
59. Capturing stereochemical information with AI: Driving stereoselectivity prediction and rational design in asymmetric catalysis
    Li Cheng, Pan‐Lin Shao, Songlin Zhao, Bo Zhang, Guichuan Xing · 2026 · Chinese Chemical Letters
60. A Selective Multi-View Representation Augmentation Framework for Crystal Property Prediction
    Haomin Yu, Jilin Hu, Kasper Tolborg, Chenjuan Guo, Mohamad Hossein Saraee, Bin Yang, Christian S. Jensen · 2026 · ACM Transactions on AI for Science
61. Chemical Language Model Applications in Medicinal Chemistry
    Gauri Mishra, Vaibhav A. Dixit · 2026 · Royal Society of Chemistry eBooks
62. Neuro-Symbolic Chemistry Reconnects Learned Molecular Representations with Reaction Rules, Biological Mechanisms, and Scientific Constraints
    Juergen Hofmann, Jan Novotny, Eva Horvathova, Lukas Novak · 2025 · Pharmacophore
63. The Applications of Machine Learning in Micro‐Nano Materials Research: From High‐Throughput Screening to Intelligent Design
    Ke Wu, Zefan Sang, Guangxun Zhang, Huan Pang · 2026 · Small
64. AI-Powered Prediction of Molecular Properties of Phytochemicals
    Iqra Riaz, Shahid Ullah Khan, Sohail · 2026 · Springer eBooks
65. The Evolution of Generative Chemistry in Medicinal Chemistry
    Rania Ehab Koshty, Manar Ahmed Shehata, Ahmed M. Gab Allah, Mohamed Bakr Zaki, Yaseen A. M. M. Elshaier · 2026 · ChemistrySelect
66. Prediction of thermomechanical coupling response of polycrystalline materials based on graph neural networks
    Hao Peng, Long Li, Kunpeng Zhang, Junjie Wang · 2026 · Applied Mathematical Modelling
67. Is One Molecular Representation Enough? A Comparative Study of Geometry-Based Featurization Methods
    Muhammad Shahzeb Ali, Shahtaj Bano · 2026 · SSRN Electronic Journal
68. Geometry-Based Atomic Representations for Reactive Combustion Chemistry
    Zhan Si, Jingjing Hu, Qiqi Zhang, Hu Ding, Haizhu Yu, Deguang Liu, Yao Fu · 2026 · Precision Chemistry
69. 3D, Structure-Based, Deep Learning Approach to Predict the Regioselectivity of Olefin Hydroformylations
    Nicholas Hadler, N. Ian Rinehart, Masha Elkin, Jeremy Nicolai, Golsa Gheibi, Jiaqing Chen, Matthew Avaylon, Ross Maciejewski, Gunther H. Weber, Michael W. Mahoney et al. · 2026 · Journal of the American Chemical Society
70. Prediction of sugar reactions in high-temperature water using natural language processing
    Ayami Koike, Haruka Minesugi, Mitsumasa Osada · 2026 · The Journal of Supercritical Fluids
71. Artificial Intelligence in Scalable Materials Synthesis and Manufacturing
    Nagababu Andraju · 2026 · AI Chemistry
72. Decoding microstructure-property relationships in polycrystals: an explainable GNN surrogate for crystal plasticity
    Ali Reza Safi, Pedro Campos, Frederic E. Bock, Benjamin Klusemann · 2026 · Machine learning for computational science and engineering
73. Progress in the interdisciplinary field of artificial intelligence and chemistry
    Shumin Zhao, Yixin Ma, Jun Wang · 2026 · Science China Chemistry
74. Starch-derived oligosaccharides as prebiotics in innovative functional foods
    Xingyuan Liu, Jiawei Tang, Xiaodan Song, 佳希 韩, Wenjun Deng, Mengxiao Tang, Ao Li, Hao Shi, Zhongbiao Tan · 2026 · Food Research International
75. GMSF: A Dual-Path Multimodal Framework for Enzyme Function Prediction via Difference Graph Encoding and Multiscale Semantic Fusion
    Xin Wayne Zhao, Haoshu Chen, Tao Zhang, Yahui Cao, Haotong Li, Zhuoran Song, Bo Li, Shuo Zheng · 2026 · Journal of Chemical Information and Modeling
76. A synthetic-data and machine-learning digital shadow foundation for end-of-life magnet recycling
    Nikolaos Sifakis, Alexandros Chachalis, George Tsinarakis, Maria Aryblia, Dimitrios Cholidis, George Arampatzis · 2026 · Measurement Digitalization
77. Enhancing pesticide-likeness prediction via multimodal deep learning ensemble framework
    Changwei Du, Chenyang Ling, Yutong Qian, Lifeng Jia, Yuan Zhang, Heqi Liu, Yuanyuan Chen · 2026 · Computers and Electronics in Agriculture
78. Artificial Intelligence-Assisted Design and Optimization of AMP–Re(CO)3 (Nano)Microgel Systems: A New Perspective in Combating Antimicrobial Resistance
    Vlad Mihai Chiriac, Andrei-Alexandru Ivu, Alina Gabriela Rusu, Alina Ghilan, Alexandru‐Mihail Serban, Alexandra Croitoriu, Loredana Elena Nita, Aurica P. Chiriac · 2026 · Gels
79. A BRAF-focused computational pipeline integrating GPT-based molecular generation, hybrid-reward reinforcement learning and retrosynthetic prioritization
    Nikoletta-Maria Koutroumpa, Konstantinos D. Papavasileiou, Haralambos Tzoupis, Charis Georgiou, Alexios N. Matralis, Georgia Melagraki, Antreas Afantitis · 2026 · Artificial Intelligence Chemistry