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ORCIDHongming Chen 0001
Person information
- affiliation: Guangdong Laboratory, Guangzhou, China
Other persons with the same name
- Hongming Chen — disambiguation page
- Hongming Chen 0002 — Peking University, Beijing, China
- Hongming Chen 0003
![[0000-0003-0966-8608]](https://dblp.org/img/orcid-mark.12x12.png "0000-0003-0966-8608")
— Zhejiang Ocean University, Zhoushan, China - Hongming Chen 0004 — Shenyang Aerospace University, China
Other persons with a similar name
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2020 – today
- 2024
[j29]Zhiguang Fan, Yuedong Yang, Mingyuan Xu, Hongming Chen:
EC-Conf: A ultra-fast diffusion model for molecular conformation generation with equivariant consistency. J. Cheminformatics 16(1): 107 (2024)- [j28]Hao Zhang, Jinchao Huang, Junjie Xie, Weifeng Huang, Yuedong Yang, Mingyuan Xu, Jinping Lei, Hongming Chen:
GRELinker: A Graph-Based Generative Model for Molecular Linker Design with Reinforcement and Curriculum Learning. J. Chem. Inf. Model. 64(3): 666-676 (2024) - 2023
- [j27]Baiqing Li, Ting Ran, Hongming Chen:
3D based generative PROTAC linker design with reinforcement learning. Briefings Bioinform. 24(5) (2023) - [j26]Qijie Chen, Haotong Sun, Haoyang Liu, Yinghui Jiang, Ting Ran, Xurui Jin, Xianglu Xiao, Zhimin Lin, Hongming Chen, Zhangming Niu:
An extensive benchmark study on biomedical text generation and mining with ChatGPT. Bioinform. 39(9) (2023) - [i3]Zhiguang Fan, Yuedong Yang, Mingyuan Xu, Hongming Chen:
Node-based Knowledge Graph Contrastive Learning for Medical Relationship Prediction. CoRR abs/2310.10138 (2023) - 2022
- [j25]Penglei Wang, Shuangjia Zheng, Yize Jiang, Chengtao Li, Junhong Liu, Chang Wen, Atanas Patronov, Dahong Qian, Hongming Chen, Yuedong Yang:
Structure-Aware Multimodal Deep Learning for Drug-Protein Interaction Prediction. J. Chem. Inf. Model. 62(5): 1308-1317 (2022) - [j24]Jie Zhang, Hongming Chen:
De Novo Molecule Design Using Molecular Generative Models Constrained by Ligand-Protein Interactions. J. Chem. Inf. Model. 62(14): 3291-3306 (2022) - [j23]Youhai Tan, Lingxue Dai, Weifeng Huang, Yinfeng Guo, Shuangjia Zheng, Jinping Lei, Hongming Chen, Yuedong Yang:
DRlinker: Deep Reinforcement Learning for Optimization in Fragment Linking Design. J. Chem. Inf. Model. 62(23): 5907-5917 (2022) - [j22]Shuangjia Zheng, Youhai Tan, Zhenyu Wang, Chengtao Li, Zhiqing Zhang, Xu Sang, Hongming Chen, Yuedong Yang:
Accelerated rational PROTAC design via deep learning and molecular simulations. Nat. Mac. Intell. 4(9): 739-748 (2022) - 2021
- [j21]Shuangjia Zheng, Zengrong Lei, Haitao Ai, Hongming Chen, Daiguo Deng, Yuedong Yang:
Deep scaffold hopping with multimodal transformer neural networks. J. Cheminformatics 13(1): 87 (2021) - [j20]Jie Zhang, Rocío Mercado, Ola Engkvist, Hongming Chen:
Comparative Study of Deep Generative Models on Chemical Space Coverage. J. Chem. Inf. Model. 61(6): 2572-2581 (2021) - [j19]Mingyuan Xu, Ting Ran, Hongming Chen:
De Novo Molecule Design Through the Molecular Generative Model Conditioned by 3D Information of Protein Binding Sites. J. Chem. Inf. Model. 61(7): 3240-3254 (2021) - [j18]Lizhao Hu, Yuyao Yang, Shuangjia Zheng, Jun Xu, Ting Ran, Hongming Chen:
Kinase Inhibitor Scaffold Hopping with Deep Learning Approaches. J. Chem. Inf. Model. 61(10): 4900-4912 (2021) - [j17]Rocío Mercado, Tobias Rastemo, Edvard Lindelöf, Günter Klambauer, Ola Engkvist, Hongming Chen, Esben Jannik Bjerrum:
Graph networks for molecular design. Mach. Learn. Sci. Technol. 2(2): 25023 (2021) - 2020
- [j16]Michael Withnall, Edvard Lindelöf, Ola Engkvist, Hongming Chen:
Building attention and edge message passing neural networks for bioactivity and physical-chemical property prediction. J. Cheminformatics 12(1): 1 (2020) - [j15]Noé Sturm, Andreas Mayr, Thanh Le Van, Vladimir I. Chupakhin, Hugo Ceulemans, Jörg K. Wegner, José Felipe Golib Dzib, Nina Jeliazkova, Yves Vandriessche, Stanislav Böhm, Vojtech Cima, Jan Martinovic, Nigel Greene, Tom Vander Aa, Thomas J. Ashby, Sepp Hochreiter, Ola Engkvist, Günter Klambauer, Hongming Chen:
Industry-scale application and evaluation of deep learning for drug target prediction. J. Cheminformatics 12(1): 26 (2020) - [j14]Josep Arús-Pous, Atanas Patronov, Esben Jannik Bjerrum, Christian Tyrchan, Jean-Louis Reymond, Hongming Chen, Ola Engkvist:
SMILES-based deep generative scaffold decorator for de-novo drug design. J. Cheminformatics 12(1): 38 (2020) - [j13]Thomas Blaschke, Josep Arús-Pous, Hongming Chen, Christian Margreitter, Christian Tyrchan, Ola Engkvist, Kostas Papadopoulos, Atanas Patronov:
REINVENT 2.0: An AI Tool for De Novo Drug Design. J. Chem. Inf. Model. 60(12): 5918-5922 (2020) - [j12]Panagiotis-Christos Kotsias, Josep Arús-Pous, Hongming Chen, Ola Engkvist, Christian Tyrchan, Esben Jannik Bjerrum:
Direct steering of de novo molecular generation with descriptor conditional recurrent neural networks. Nat. Mach. Intell. 2(5): 254-265 (2020)
2010 – 2019
- 2019
- [j11]Josep Arús-Pous, Thomas Blaschke, Silas Ulander, Jean-Louis Reymond, Hongming Chen, Ola Engkvist:
Exploring the GDB-13 chemical space using deep generative models. J. Cheminformatics 11(1): 20:1-20:14 (2019) - [j10]Oliver Laufkötter, Noé Sturm, Jürgen Bajorath, Hongming Chen, Ola Engkvist:
Combining structural and bioactivity-based fingerprints improves prediction performance and scaffold hopping capability. J. Cheminformatics 11(1): 54:1-54:14 (2019) - [j9]Josep Arús-Pous, Simon Johansson, Oleksii Prykhodko, Esben Jannik Bjerrum, Christian Tyrchan, Jean-Louis Reymond, Hongming Chen, Ola Engkvist:
Randomized SMILES strings improve the quality of molecular generative models. J. Cheminformatics 11(1): 71:1-71:13 (2019) - [j8]Oleksii Prykhodko, Simon Johansson, Panagiotis-Christos Kotsias, Josep Arús-Pous, Esben Jannik Bjerrum, Ola Engkvist, Hongming Chen:
A de novo molecular generation method using latent vector based generative adversarial network. J. Cheminformatics 11(1): 74 (2019) - [j7]Noé Sturm, Jiangming Sun, Yves Vandriessche, Andreas Mayr, Günter Klambauer, Lars Carlsson, Ola Engkvist, Hongming Chen:
Application of Bioactivity Profile-Based Fingerprints for Building Machine Learning Models. J. Chem. Inf. Model. 59(3): 962-972 (2019) - [c3]Jiangming Sun, Nina Jeliazkova, Vladimir I. Chupakhin, José Felipe Golib Dzib, Lars Carlsson, Jörg K. Wegner, Hugo Ceulemans, Ivan Georgiev, Vedrin Jeliazkov, Nikolay T. Kochev, Thomas J. Ashby, Hongming Chen:
ExCAPE-DB: An Integrated Large Scale Dataset Facilitating Big Data Analysis in Chemogenomics. BNAIC/BENELEARN 2019 - [c2]Josep Arús-Pous, Simon Johansson, Oleksii Prykhodko, Esben Jannik Bjerrum, Christian Tyrchan, Jean-Louis Reymond, Hongming Chen, Ola Engkvist:
Improving Deep Generative Models with Randomized SMILES. ICANN (Workshop) 2019: 747-751 - [c1]Michael Withnall, Edvard Lindelöf, Ola Engkvist, Hongming Chen:
Attention and Edge Memory Convolution for Bioactivity Prediction. ICANN (Workshop) 2019: 752-757 - 2017
- [j6]Jiangming Sun, Nina Jeliazkova, Vladimir I. Chupakhin, José Felipe Golib Dzib, Ola Engkvist, Lars Carlsson, Jörg K. Wegner, Hugo Ceulemans, Ivan Georgiev, Vedrin Jeliazkov, Nikolay T. Kochev, Thomas J. Ashby, Hongming Chen:
ExCAPE-DB: an integrated large scale dataset facilitating Big Data analysis in chemogenomics. J. Cheminformatics 9(1): 17:1-17:9 (2017) - [j5]Jiangming Sun, Nina Jeliazkova, Vladimir I. Chupakhin, José Felipe Golib Dzib, Ola Engkvist, Lars Carlsson, Jörg K. Wegner, Hugo Ceulemans, Ivan Georgiev, Vedrin Jeliazkov, Nikolay T. Kochev, Thomas J. Ashby, Hongming Chen:
Erratum to: ExCAPE-DB: an integrated large scale dataset facilitating Big Data analysis in chemogenomics. J. Cheminformatics 9(1): 41:1 (2017) - [j4]Marcus Olivecrona, Thomas Blaschke, Ola Engkvist, Hongming Chen:
Molecular de-novo design through deep reinforcement learning. J. Cheminformatics 9(1): 48:1-48:14 (2017) - [j3]Jiangming Sun, Lars Carlsson, Ernst Ahlberg, Ulf Norinder, Ola Engkvist, Hongming Chen:
Applying Mondrian Cross-Conformal Prediction To Estimate Prediction Confidence on Large Imbalanced Bioactivity Data Sets. J. Chem. Inf. Model. 57(7): 1591-1598 (2017) - [i2]Marcus Olivecrona, Thomas Blaschke, Ola Engkvist, Hongming Chen:
Molecular De Novo Design through Deep Reinforcement Learning. CoRR abs/1704.07555 (2017) - [i1]Thomas Blaschke, Marcus Olivecrona, Ola Engkvist, Jürgen Bajorath, Hongming Chen:
Application of generative autoencoder in de novo molecular design. CoRR abs/1711.07839 (2017) - 2010
- [j2]Hongming Chen, Yidong Yang, Ola Engkvist:
Molecular Topology Analysis of the Differences between Drugs, Clinical Candidate Compounds, and Bioactive Molecules. J. Chem. Inf. Model. 50(12): 2141-2150 (2010)
2000 – 2009
- 2009
- [j1]Hongming Chen, Ulf Borjesson, Ola Engkvist, Thierry Kogej, Mats Svensson, Niklas Blomberg, Dirk Weigelt, Jeremy N. Burrows, Tim Lange:
ProSAR: A New Methodology for Combinatorial Library Design. J. Chem. Inf. Model. 49(3): 603-614 (2009)
Coauthor Index
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