学术著作
出版书籍
宋弢，曾湘祥，王爽，王建民，智能药物研发，清华大学出版社，2022（国内首本人工智能药物研发教材，京东购买链接）
Pan Zheng, Shudong Wang, Xun Wang and Xiangxiang Zeng, Artificial Intelligence in Bioinformatics and Drug Repurposing: Methods and Applications. 2022.
Xiangxiang Zeng, Alfonso Rodríguez-Patón, Molecular Computing and Bioinformatics, MDPI, 2019.
邹权，陈启安，曾湘祥，刘向荣，系统生物学中的网络分析方法，西安电子科技大学出版社，2015.
潘林强，曾湘祥，宋弢，膜计算导论，华中科技大学出版社，2012.
2025年论文
[33] Zixu Wang, Yangyang Chen, Pengsen Ma, Zhou Yu, Jianmin Wang, Yuansheng Liu, Xiucai Ye, Tetsuya Sakurai, Xiangxiang Zeng, Image-Based Generation for Molecule Design with SketchMol, Nature Machine Intelligence, 2025. (Nature子刊，智药邦报道)
[32] Zhonghao Ren, Xiangxiang Zeng, et al. Predicting rare drug-drug interaction events with dual-granular structure-adaptive and pair variational representation. Nature Communications 16, 3997 (2025). (Nature子刊，知乎报道)
[31] Peng Zhou, Pengsen Mao, Lianmin Wang, Xibao Cai, Haitao Huang, Wei Liu, Longyue Wang, Lai Hou Tim, Xiangxiang Zeng, Large Language and Protein Assistant for Protein Protein Interactions Prediction, ACL 2025. (CCF A)
[30] Fang Wu, Zhengyuan Zhou, Shuting Jin, Xiangxiang Zeng, Jure Leskovec, Jinbo Xu, Surface-based Molecular Design with Multi-modal Flow Matching, KDD 2025. (CCF A)
[29] Ruizhe Chen, Dongyu Xue, Xiangxin Zhou, Zaixiang Zheng, Xiangxiang Zeng, Quanquan Gu, An All-Atom Generative Model for Designing Protein Complexes. ICML 2025. (CCF A)
[28] Hongxin Xiang, Jun Xia, Xin Jin, Wenjie Du, Li Zeng, Xiangxiang Zeng, Electron Density-enhanced Molecular Geometry Learning, IJCAI 2025. (CCF A)
[27] Qingrui Liu, Xuan Lin, Hongxin Xiang , Daojian Zeng, Xiangxiang Zeng，Enhancing Chemical Reaction and Retrosynthesis Prediction with Large Language Model and Dual-task Learning，IJCAI 2025. (CCF A)
[26] Tengfei Ma, Xiang Song, Wen Tao, Mufei Li, Jiani Zhang, Xiaoqin Pan, Jianxin Lin, Bosheng Song, Xiangxiang Zeng, KGExplainer: Towards Exploring Connected Subgraph Explanations for Knowledge Graph Completion, ICLR 2025.
[25] Tengfei Ma, Chen Yujie, Liang Wang, Xuan Lin, Bosheng Song, Xiangxiang Zeng, S2DN: Learning to Denoise Unconvincing Knowledge for Inductive Knowledge Graph Completion, AAAI 2025. (CCF A, oral)
[24] Yiping Liu, Jiahao Yang, Xuanbai Ren, Zhang Xinyi, Yuansheng Liu, Bosheng Song, Xiangxiang Zeng, Hisao Ishibuchi, Multi-Objective Molecular Design Through Learning Latent Pareto Set, AAAI 2025. (CCF A)
2024年论文
[23] Pengyong Li, Kaihao Zhang, Tianxiao Liu, Ruiqiang Lu, Yangyang Chen, Xiaojun Yao, Lin Gao, Xiangxiang Zeng, A Deep Learning Approach for Rational Ligand Generation with Toxicity Control via Reactive Building Blocks, Nature Computational Science. 2024. (Nature子刊，基金委报道，NCS评论)
[22] Hongxin Xiang, Li Zeng, Linlin Hou, Kenli Li, Zhimin Fu, Yunguang Qiu, Ruth Nussinov, Jianying Hu, Michal Rosen-Zvi, Xiangxiang Zeng, Feixiong Cheng, A Molecular Video-derived Foundation Model Streamlines Scientific Drug Discovery, Nature Communications, 2024. (Nature子刊，机器之心报道)
[21] Tingting Li, Xuanbai Ren, Xiaoli Luo, Zhuole Wang, Zhenlu Li, Xiaoyan Luo, Jun Shen, Yun Li, Dan Yuan,Ruth Nussinov, Xiangxiang Zeng, Junfeng Shi, Feixiong Cheng, A Foundation Model Identifies Broad-Spectrum Antimicrobial Peptides against Drug-Resistant Bacterial Infection, Nature Communications, 2024, doi.org/10.1038/s41467-024-51933-2. (Nature子刊，湖南日报报道)
[20] Houtim Lai, Longyue Wang, Ruiyuan Qian, Junhong Huang, Peng Zhou, Geyan Ye, Fandi Wu, Fang Wu, Xiangxiang Zeng, Wei Liu. Interformer: an interaction-aware model for protein-ligand docking and affinity prediction. Nature Communications 15, 10223, 2024. (Nature子刊)
[19] Xuanbai Ren, J. Wei, X. Luo, Y. Liu, K. Li, Q. Zhang, X. Gao, S. Yan, X. Wu, X. Jiang, M. Liu, D. Cao, L. Wei, Xiangxiang Zeng, Junfeng Shi, HydrogelFinder: A Foundation Model for Efficient Self-Assembling Peptide Discovery Guided by Non-Peptidal Small Molecules. Advanced Science, 2024, 11, 2400829. (IF: 15.1)
[18] Hongxin Xiang, Shuting Jin, Jun Xia, Man Zhou, Jianmin Wang, Li Zeng, Xiangxiang Zeng. An Image-enhanced Molecular Graph Representation Learning Framework, IJCAI, 2024 (CCF A)
[17] Taisong Jin; Xixi Yang; Zhengtao Yu, Han Luo, Yongmei Zhang, Feiran Jie, Xiangxiang Zeng, Min Jiang, WalkGAN: Network Representation Learning With Sequence-Based Generative Adversarial Networks, IEEE Transactions on Neural Networks and Learning Systems, 2024, 35(4), 5684-5694.
[16] Jiacai Yi, Shaohua Shi, Li Fu, Ziyi Yang, Pengfei Nie, Aiping Lu, Chengkun Wu, Yafeng Deng, Changyu Hsieh, Xiangxiang Zeng, Tingjun Hou, Dongsheng Cao. OptADMET: a web-based tool for substructure modifications to improve ADMET properties of lead compounds, Nature Protocols, 2024, 19(4):1105-1121. (Nature子刊)
2023年论文
[15] Yu Wang, Chao Pang, Yuzhe Wang, Junrui Jin, Jingjie Zhang, Xiangxiang Zeng, Ran Su, Quan Zou, Leyi Wei. Retrosynthesis prediction with an interpretable deep-learning framework based on molecular assembly tasks. Nature Communications 14, 6155 (2023). (Nature子刊)
[14] Shugao Chen, Ziyao Li, Xiangxiang Zeng, Guolin Ke. Amalga: Designable Protein Backbone Generation with Folding and Inverse Folding Guidance, NeurIPS, 2023. (CCF A)
[13] Bin Wu, Jinyuan Fang, Xiangxiang Zeng, Shangsong Liang, Qiang Zhang, Adaptive Compositional Continual Meta-Learning, ICML 2023 (CCF A)
[12] Xixi Yang, Li Fu, Yafeng Deng, Yuansheng Liu, Dongsheng Cao, Xiangxiang Zeng, GPMO: Gradient perturbation-based contrastive learning for molecule Optimization , IJCAI 2023. (CCF A)
[11] Peng Zhou, Zongqian Wu, Xiangxiang Zeng, Guoqiu Wen, Junbo Ma, Xiaofeng Zhu, Totally Dynamic Hypergraph Neural Network , IJCAI 2023. (CCF A)
[10] Chunyan Li, JunfengYao, Jinsong Su, Zhaoyang Liu, Xiangxiang Zeng, Chenxi Huang, LagNet: Deep Lagrangian Mechanics for Plug-and-Play Molecular Representation Learning, AAAI 2023. (CCF A)
[9] Junlin Xu, Jielin Xu, Yajie
Meng, Changcheng Lu, Lijun Cai, Xiangxiang Zeng, Ruth Nussinov, Graph Embedding and Gaussian Mixture Variational
Autoencoder Network for End-to-End Analysis of Single-Cell RNA-Sequencing Data. Cell Reports Methods. 2023. (Cell子刊)
[8] Bosheng Song, Kenli Li, David Orellana-Martín, Xiangxiang Zeng, Mario J. Pérez-Jiménez, Tissue P systems with states in cells, IEEE Transactions on Computers, 2023, 72(9), 2561-2570. (CCF A)
[7] Bosheng Song, Kenli Li, Xiangxiang Zeng, Mario J. Pérez-Jiménez, Claudio Zandron, Monodirectional evolutional symport tissue P systems with channel states and cell division, SCIENCE CHINA Information Sciences, 2023, 66(3), 139104. (CCF A)
2022年论文
[6] Xiangxiang Zeng, Hongxin Xiang, Linhui Yu, J Wang, Kenli Li, R Nussinov, Feixiong Cheng. Accurate prediction of molecular properties and molecular targets usinga self-supervised image representation learning framework. Nature Machine Intelligence.2022. (Nature子刊)
[5] Xiangxiang Zeng, Fei Wang, Yuan Luo, Seung-gu Kang, Jian Tang, Felice C. Lightstone, Evandro F. Fang, Wendy Cornell, Ruth Nussinov, Feixiong Cheng, Deep Generative Molecular Design Reshapes Drug Discovery, Cell Reports Medicine, 2022. (Cell子刊)
[4] Xiaoqin Pan, Xuan Lin, Dongsheng Cao, Xiangxiang Zeng, Phillipe Yu, Lifang He, Feixiong Cheng. Deep learning for drug repurposing:Methods,databases, and applications. WIREs Comput Mol Sci. 2022; e1597. (IF:25.11)
[3] Yanyan Li, Bosheng Song, Xiangxiang Zeng, Rule synchronization for monodirectional tissue-like P systems with channel states, Information and Computation, 2022, 285, 104895. (CCF A)
[2] Bosheng Song, Kenli Li, Xiangxiang Zeng, Monodirectional evolutional symport tissue P systems with promoters and cell division, IEEE Transactions on Parallel and Distributed Systems, 2022, 33(2), 332-342. (CCF A)
[1] Chunyan Li, Junfeng Yao, Wei Wei, Zhangming Niu, Xiangxiang Zeng, Jin Li, Jianmin Wang, Geometry-Based Molecular Generation With Deep Constrained Variational Autoencoder, IEEE Transactions on Neural Networks and Learning Systems, doi: 10.1109/TNNLS.2022.3147790.
更多论文请见：https://scholar.google.com/citations?user=B20HBMIAAAAJ&hl=en
科研项目
招生说明
学生培养
指导硕士
2010级：吴小英（厦门电信云，CTO）
2011级：王旭波（澳大利亚UNSW大学读博，计算机学科世界前20，悉尼大学工作）
2012级：廖原路（招行软开）
2013级：李友（柔宇科技）
2013级：李子铭（获两次国奖共4万元，美国亚马逊工作）
2013级：索娟（获国奖2万元，厦门大学翔安医院）
2013级：李金金（获两次国奖共4万元，厦门美团）
2013级：谢思发（获国奖2万元，深圳腾讯）
2014级：张璇（获两次国奖共4万元，澳洲悉尼科技大学读博，工作于Victor Chang Cardiac Research Institute）
2014级：丁宁翔（十佳共青团员，华为奖学金，优秀毕业论文，中国人民银行）
2014级：张菘洺（获国奖2万元，上海花旗银行）
2015级：林伟（获国奖2万元，厦门建行软开）
2015级：邴嘉欣（厦门快乐学习）
2015级：陈聪（厦航）
2015级：Israel（卢旺达）
2015级：贺语盈（与闵小平老师联合指导，顺丰科技）
2015级：张谋钊（与闵小平老师联合指导，华为奖学金，厦航）
2016级：金淑婷（获国奖2万元，厦门大学读博）
2016级：林佳伟（Aibee创业公司）
2016级：刘丽（获国奖2万元，华为奖学金8000元，华为）
2016级：汪文（阿里）
2017级：杜妍孜(Unity)
2017级：罗菡（华为）
2017级：章茜茜（华为）
2017级：朱思怡（获两次国奖共4万元，华为特别offer）
2017级：林盈来（腾讯）
2018级：钟玥（获国家奖学金2万元，Amazon AI实习，字节跳动）
2018级：叶聪敏（获国家奖学金2万元，字节跳动实习，滴滴）
2019级：马腾飞(Amazon AI实习，华为实习，阿里工作）
2019级：罗潇澧（阿拉丁实习，百图生科实习，药明康德工作）
2019级：潘晓琴（阿里实习，蚂蚁金服工作）
2019级：陈雨洁（搜狗实习，字节跳动工作）
2019级：俞琳荟（哔哩哔哩实习，韶关学院工作）
2019级：罗晓妍（德睿实习，长沙银行工作）
2020级：董靖鑫（获国家奖学金2万元，东方理工研究院实习，阿德莱德大学读博）
2020级：涂心琪（联想实习，联想工作）
2020级：李梓盟（微软亚研实习，阿里工作）
2021级：周珍冉，杨慧丹，陶雯，赵宸，陈述高
2022级：陈睿哲，陈泽慧，刘名权，程志祥
2023级：谢聆轩，甄茁文，李超逸
2024级：黄海涛，向成睿，陈全超
指导博士
2014级：徐航（与曾文华教授联合指导，新西兰维多利亚大学博后）
2014级：陈旭（与王备战教授联合指导，美国北卡教堂山分校博士后）
2016级：姜晶（与电子科技大学邹权教授联合指导，OSU联合培养，德州大学圣安东尼分校博士后）
2019级：金淑婷（与厦大刘向荣教授联合指导，德睿智药和宇耀生物实习，武汉科技大学任教）
2020级：杨喜喜（德睿智药实习，碳硅智能实习，湘潭大学工作）
2021级：向鸿鑫（宇耀生物实习），卢长城
2022级：任宣百
2023级：任忠豪，马鹏森
2024级：蔡禧宝
指导博士后
2016级：Francis George C. Cabarle（获外专局外国青年人才项目资助，出站后于菲律宾大学任教）
2019级：付祥政（湖南大学博士毕业，获国自科青年基金，博士后基金，香港浸会大学博士后）
2020级：潘楚（湖南大学博士毕业，获湖南大学博士后重点资助，国自科青年基金）
2020级：彭勇（中南大学博士毕业，复星医药高管，在职博士后）
2021级：姜晶（厦门大学博士毕业，获湖南大学博士后重点资助，国自科青年基金）
2021级：许俊林（湖南大学博士毕业，获湖南大学博士后重点资助，国自科青年基金）
2022级：刘莹（湖南大学博士毕业，获湖南大学博士后重点资助，国自科青年基金）
2023级：尚奕帆（筑波大学博士毕业，获湖南大学博士后重点资助，入选香江学者）
2024级：杨心宇（入选国家海外引才项目）
指导本科生
2013级：邓高山（发表国际会议论文一篇，南加州大学留学，世界排名前三十，硅谷工作）
2014级：孟祥毅（发表CCF B类会议一篇，2018年香港城市大学攻读博士学位）
2015级：陈洪杰（发表CCF B类会议一篇，2019年美国弗吉利亚理工攻读博士学位）
2016级：张杨康（Amazon AI实习，2020年保送浙江大学研究生）
2019级：洪滢聪（湖南大学理科实验班）
2022级：戴亦凡（获国家奖学金）、喻迪
荣誉与获奖
