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2020 – today
- 2024
[j7]Cheng Zhu
, Chengyun Zhang, Tianfeng Shang, Chenhao Zhang, Silong Zhai, Lujing Cao, Zhenyu Xu, Zhihao Su, Ying Song, An Su, Chengxi Li, Hongliang Duan:
GAPS: a geometric attention-based network for peptide binding site identification by the transfer learning approach. Briefings Bioinform. 25(4) (2024)- [j6]Chenglin Yin, Ruheng Wang, Jianbo Qiao, Hua Shi, Hongliang Duan, Xinbo Jiang, Saisai Teng, Leyi Wei:
NanoCon: contrastive learning-based deep hybrid network for nanopore methylation detection. Bioinform. 40(2) (2024) - [j5]Chengwei Zhang, Yushuang Zhai, Ziyang Gong, Hongliang Duan, Yuan-Bin She, Yun-Fang Yang, An Su:
Transfer learning across different chemical domains: virtual screening of organic materials with deep learning models pretrained on small molecule and chemical reaction data. J. Cheminformatics 16(1): 89 (2024) - 2023
- [j4]Zhipeng Wu, Yejian Wu, Cheng Zhu, Xinyi Wu, Silong Zhai, Xinqiao Wang, Zhihao Su, Hongliang Duan:
Efficient Computational Framework for Target-Specific Active Peptide Discovery: A Case Study on IL-17C Targeting Cyclic Peptides. J. Chem. Inf. Model. 63(24): 7655-7668 (2023) - 2022
- [j3]Xinqiao Wang, Chuansheng Yao, Yun Zhang, Jiahui Yu, Haoran Qiao, Chengyun Zhang, Yejian Wu, Renren Bai, Hongliang Duan:
From theory to experiment: transformer-based generation enables rapid discovery of novel reactions. J. Cheminformatics 14(1): 60 (2022) - [j2]Zhipeng Wu, Xiang Cai, Chengyun Zhang, Haoran Qiao, Yejian Wu, Yun Zhang, Xinqiao Wang, Haiying Xie, Feng Luo, Hongliang Duan:
Self-Supervised Molecular Pretraining Strategy for Low-Resource Reaction Prediction Scenarios. J. Chem. Inf. Model. 62(19): 4579-4590 (2022) - 2021
- [j1]Yu Zhang, Xiaofei Di, Hongliang Duan, Xi Yang, Peng Wu, Baoguo Shan:
Outage Performance of Full-Duplex Relay Networks Powered by RF Power Station in Ubiquitous Electric Internet of Things. Wirel. Commun. Mob. Comput. 2021: 9983433:1-9983433:9 (2021)
2010 – 2019
- 2019
- [i1]Hongliang Duan, Ling Wang, Chengyun Zhang, Jianjun Li:
Retrosynthesis with Attention-Based NMT Model and Chemical Analysis of the "Wrong" Predictions. CoRR abs/1908.00727 (2019)
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