Hongming Chen - RankMe

39 papers Journal 36Unranked 3

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	A 3D pocket-aware lead optimization model with knowledge guidance and its application for discovery of new glutaminyl cyclase inhibitors. Briefings Bioinform. Anjie Qiao, Yuting Chen, Junjie Xie, Weifeng Huang, Hao Zhang, Qirui Deng, Jiahua Rao, Ji Deng, Fanbo Meng, Zhen Wang, Mingyuan Xu, Hongming Chen, Jiancong Xie, Shuangjia Zheng, Yuedong Yang, Guo-Bo Li, Jinping Lei
2025	J	`jnl`	Discovery of Novel MsbA Inhibitors with a Bivalent Molecular Generative Model. J. Chem. Inf. Model. Haodi Qiu, Lei Wang, Baiqing Li, Song Wu, Yadong Chen, Ting Ran, Jie Xia, Hongming Chen
2025	J	`jnl`	NA-DB: An Online Database of Nucleoside Analogues. J. Chem. Inf. Model. Haolin Luo, Ting Ran, Ling Wang, Hongming Chen
2024	J	`jnl`	EC-Conf: A ultra-fast diffusion model for molecular conformation generation with equivariant consistency. J. Cheminformatics Zhiguang Fan, Yuedong Yang, Mingyuan Xu, Hongming Chen
2024	J	`jnl`	GRELinker: A Graph-Based Generative Model for Molecular Linker Design with Reinforcement and Curriculum Learning. J. Chem. Inf. Model. Hao Zhang, Jinchao Huang, Junjie Xie, Weifeng Huang, Yuedong Yang, Mingyuan Xu, Jinping Lei, Hongming Chen
2024	J	`jnl`	How Good are Current Pocket-Based 3D Generative Models?: The Benchmark Set and Evaluation of Protein Pocket-Based 3D Molecular Generative Models. J. Chem. Inf. Model. Haoyang Liu, Yifei Qin, Zhangming Niu, Mingyuan Xu, Jiaqiang Wu, Xianglu Xiao, Jinping Lei, Ting Ran, Hongming Chen
2023	J	`jnl`	3D based generative PROTAC linker design with reinforcement learning. Briefings Bioinform. Baiqing Li, Ting Ran, Hongming Chen
2023	J	`jnl`	An extensive benchmark study on biomedical text generation and mining with ChatGPT. Bioinform. Qijie Chen, Haotong Sun, Haoyang Liu, Yinghui Jiang, Ting Ran, Xurui Jin, Xianglu Xiao, Zhimin Lin, Hongming Chen, Zhangming Niu
2023	J	`jnl`	Node-based Knowledge Graph Contrastive Learning for Medical Relationship Prediction. CoRR Zhiguang Fan, Yuedong Yang, Mingyuan Xu, Hongming Chen
2022	J	`jnl`	Accelerated rational PROTAC design via deep learning and molecular simulations. Nat. Mac. Intell. Shuangjia Zheng, Youhai Tan, Zhenyu Wang, Chengtao Li, Zhiqing Zhang, Xu Sang, Hongming Chen, Yuedong Yang
2022	J	`jnl`	DRlinker: Deep Reinforcement Learning for Optimization in Fragment Linking Design. J. Chem. Inf. Model. Youhai Tan, Lingxue Dai, Weifeng Huang, Yinfeng Guo, Shuangjia Zheng, Jinping Lei, Hongming Chen, Yuedong Yang
2022	J	`jnl`	Structure-Aware Multimodal Deep Learning for Drug-Protein Interaction Prediction. J. Chem. Inf. Model. Penglei Wang, Shuangjia Zheng, Yize Jiang, Chengtao Li, Junhong Liu, Chang Wen, Atanas Patronov, Dahong Qian, Hongming Chen, Yuedong Yang
2021	J	`jnl`	Comparative Study of Deep Generative Models on Chemical Space Coverage. J. Chem. Inf. Model. Jie Zhang, Rocío Mercado, Ola Engkvist, Hongming Chen
2021	J	`jnl`	De Novo Molecule Design Through the Molecular Generative Model Conditioned by 3D Information of Protein Binding Sites. J. Chem. Inf. Model. Mingyuan Xu, Ting Ran, Hongming Chen
2021	J	`jnl`	Deep scaffold hopping with multimodal transformer neural networks. J. Cheminformatics Shuangjia Zheng, Zengrong Lei, Haitao Ai, Hongming Chen, Daiguo Deng, Yuedong Yang
2021	J	`jnl`	Graph networks for molecular design. Mach. Learn. Sci. Technol. Rocío Mercado, Tobias Rastemo, Edvard Lindelöf, Günter Klambauer, Ola Engkvist, Hongming Chen, Esben Jannik Bjerrum
2021	J	`jnl`	Kinase Inhibitor Scaffold Hopping with Deep Learning Approaches. J. Chem. Inf. Model. Lizhao Hu, Yuyao Yang, Shuangjia Zheng, Jun Xu, Ting Ran, Hongming Chen
2020	J	`jnl`	Building attention and edge message passing neural networks for bioactivity and physical-chemical property prediction. J. Cheminformatics Michael Withnall, Edvard Lindelöf, Ola Engkvist, Hongming Chen
2020	J	`jnl`	Direct steering of de novo molecular generation with descriptor conditional recurrent neural networks. Nat. Mach. Intell. Panagiotis-Christos Kotsias, Josep Arús-Pous, Hongming Chen, Ola Engkvist, Christian Tyrchan, Esben Jannik Bjerrum
2020	J	`jnl`	Industry-scale application and evaluation of deep learning for drug target prediction. J. Cheminformatics 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
2020	J	`jnl`	REINVENT 2.0: An AI Tool for De Novo Drug Design. J. Chem. Inf. Model. Thomas Blaschke, Josep Arús-Pous, Hongming Chen, Christian Margreitter, Christian Tyrchan, Ola Engkvist, Kostas Papadopoulos, Atanas Patronov
2020	J	`jnl`	SMILES-based deep generative scaffold decorator for de-novo drug design. J. Cheminformatics Josep Arús-Pous, Atanas Patronov, Esben Jannik Bjerrum, Christian Tyrchan, Jean-Louis Reymond, Hongming Chen, Ola Engkvist
2019	J	`jnl`	A de novo molecular generation method using latent vector based generative adversarial network. J. Cheminformatics Oleksii Prykhodko, Simon Johansson, Panagiotis-Christos Kotsias, Josep Arús-Pous, Esben Jannik Bjerrum, Ola Engkvist, Hongming Chen
2019	J	`jnl`	Application of Bioactivity Profile-Based Fingerprints for Building Machine Learning Models. J. Chem. Inf. Model. Noé Sturm, Jiangming Sun, Yves Vandriessche, Andreas Mayr, Günter Klambauer, Lars Carlsson, Ola Engkvist, Hongming Chen
2019	—	`conf`	Attention and Edge Memory Convolution for Bioactivity Prediction. ICANN (Workshop) Michael Withnall, Edvard Lindelöf, Ola Engkvist, Hongming Chen
2019	J	`jnl`	Combining structural and bioactivity-based fingerprints improves prediction performance and scaffold hopping capability. J. Cheminformatics Oliver Laufkötter, Noé Sturm, Jürgen Bajorath, Hongming Chen, Ola Engkvist
2019	—	`conf`	ExCAPE-DB: An Integrated Large Scale Dataset Facilitating Big Data Analysis in Chemogenomics. BNAIC/BENELEARN 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
2019	J	`jnl`	Exploring the GDB-13 chemical space using deep generative models. J. Cheminformatics Josep Arús-Pous, Thomas Blaschke, Silas Ulander, Jean-Louis Reymond, Hongming Chen, Ola Engkvist
2019	—	`conf`	Improving Deep Generative Models with Randomized SMILES. ICANN (Workshop) Josep Arús-Pous, Simon Johansson, Oleksii Prykhodko, Esben Jannik Bjerrum, Christian Tyrchan, Jean-Louis Reymond, Hongming Chen, Ola Engkvist
2019	J	`jnl`	Randomized SMILES strings improve the quality of molecular generative models. J. Cheminformatics Josep Arús-Pous, Simon Johansson, Oleksii Prykhodko, Esben Jannik Bjerrum, Christian Tyrchan, Jean-Louis Reymond, Hongming Chen, Ola Engkvist
2017	J	`jnl`	Application of generative autoencoder in de novo molecular design. CoRR Thomas Blaschke, Marcus Olivecrona, Ola Engkvist, Jürgen Bajorath, Hongming Chen
2017	J	`jnl`	Applying Mondrian Cross-Conformal Prediction To Estimate Prediction Confidence on Large Imbalanced Bioactivity Data Sets. J. Chem. Inf. Model. Jiangming Sun, Lars Carlsson, Ernst Ahlberg, Ulf Norinder, Ola Engkvist, Hongming Chen
2017	J	`jnl`	Erratum to: ExCAPE-DB: an integrated large scale dataset facilitating Big Data analysis in chemogenomics. J. Cheminformatics 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
2017	J	`jnl`	ExCAPE-DB: an integrated large scale dataset facilitating Big Data analysis in chemogenomics. J. Cheminformatics 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
2017	J	`jnl`	Molecular De Novo Design through Deep Reinforcement Learning. CoRR Marcus Olivecrona, Thomas Blaschke, Ola Engkvist, Hongming Chen
2017	J	`jnl`	Molecular de-novo design through deep reinforcement learning. J. Cheminformatics Marcus Olivecrona, Thomas Blaschke, Ola Engkvist, Hongming Chen
2013	J	`jnl`	Beyond the Scope of Free-Wilson Analysis: Building Interpretable QSAR Models with Machine Learning Algorithms. J. Chem. Inf. Model. Hongming Chen, Lars Carlsson, Mats Eriksson, Péter L. Várkonyi, Ulf Norinder, Ingemar Nilsson
2010	J	`jnl`	Molecular Topology Analysis of the Differences between Drugs, Clinical Candidate Compounds, and Bioactive Molecules. J. Chem. Inf. Model. Hongming Chen, Yidong Yang, Ola Engkvist
2009	J	`jnl`	ProSAR: A New Methodology for Combinatorial Library Design. J. Chem. Inf. Model. Hongming Chen, Ulf Borjesson, Ola Engkvist, Thierry Kogej, Mats Svensson, Niklas Blomberg, Dirk Weigelt, Jeremy N. Burrows, Tim Lange