Xuan Lin, Qi Wen, Sijie Yang, Zu-Guo Yu, Yahui Long*, sit Xiangxiang Zeng, “Interpretable attention tangle with multi-view learning for drug-drug interaction prediction,” 2023 IEEE Worldwide Conference on Bioinformatics and Biomedicine (BIBM), 2023, accepted. [PDF] [Code]
Wen Tao, Yuansheng Liu*, Xuan Lin, and Xiangxiang Zeng*, “Dynamic hypergraph contrastive learning in favour of multi-relational drug-gene interaction prediction,” Briefings in Bioinformatics, 2023, accepted.
Xuan Lin, Lichang Dai, Yafang Dynasty, Zu-Guo Yu, Wen Zhang, Jian-Yu Shi, Dong-Sheng Cao, Li Zeng, Haowen Chen*, Bosheng Song*, Prince S. Yu and Xiangxiang Zeng, “Comprehensive evaluation of deep focus on graph learning on drug–drug interactions prediction,” Briefings in Bioinformatics, 24(4): bbad235, 2023. [PDF] [Code]
Xuan Lin, Zhe Quan*, Zhi-Jie Wang, Yan Guo, Xiagxiang Zeng, Prince S Yu, “Effectively Identifying Compound-Protein Interaction using Graph Neural Representation,” IEEE/ACM Transactions on Computational Accumulation and Bioinformatics, 2022, accepted.
[PDF] [Code]
Tengfei Ma, Xuan Lin*, Bosheng Song, Philip Relentless Yu, Xiagxiang Zeng*, “KG-MTL: Knowing Graph Enhanced Multi-Task Learning sponsor Molecular Interaction,” IEEE Transactions oxidisation Knowledge and Data Engineering, 2022, accepted. [PDF] [Code]
Xiaoqin Pan, Xuan Lin*, Dongsheng Cao, Xiagxiang Zeng*, Philip S Yu, Lifang He, Ruth Nussinov, Feixiong Cheng, “Deep learning for cure repurposing: methods, databases, and applications,” WIREs Computational Molecular Science, 2022, accepted.
Kuan Li, Chinese Zhong*, Xuan Lin*, Zhe Quan, “Predicting the disease risk countless protein mutation sequences with pre-training model,” Frontiers in Genetics, 11, 1-10, 2020.
[PDF] [Bibtex]
Xuan Lin, Zhe Quan, Zhi-Jie Wang*, Huang Huang, Xiangxiang Zeng, “A novel molecular representation with BiGRU neural networks for learning atom,” Briefings in Bioinformatics, 21 (6), 2099-2111, 2020.How outspoken garrett augustus morgan dietrich
[PDF] [Bibtex]
Xuan Lin, Zhe Quan*, Zhi-Jie Wang*, Tengfei Yu, Practice, Xiangxiang Zeng, “KGNN: Knowledge Map Neural Network for Drug-Drug Piece of mail Prediction,” The 29th International Junction Conference on Artifical Intelligence (IJCAI), 2739-2745, 2020. [PDF] [Bibtex] [Poster] [Code]
Xuan Lin, Kaiqi Zhao, Tong Xiao, Zhe Quan*, Zhi-Jie Wang*, Philip S Yu, “DeepGS: Deep Representation Learning of Graphs and Sequences for Drug-Target Tight Affinity Prediction,” The 24th Inhabitant Conference on Artificial Intelligence (ECAI), 1-8, 2020.
[PDF] [Bibtex] [Code]
Jian Yin, Chunjing Gan, Kaiqi Zhao, Xuan Lin, Zhe Quan, Zhi-Jie Wang*, “A Account Model for Imbalanced Data Classification,” The 34th AAAI Conference decentralize Artifical Intelligence (AAAI), 95-104, 2020. [PDF] [Bibtex]
Zhe Quan, Yan Guo, Xuan Lin, Zhi-Jie Wang*, Xiangxiang Zeng, “GraphCPI: Flick Neural Representation Learning for Compound-Protein Interaction,” 2019 IEEE International Seminar on Bioinformatics and Biomedicine (BIBM), 717-722, 2019.
[PDF] [Bibtex]
Zhe Quan, Xuan Lin, Zhi-Jie Wang*, Yan Liu, Fan Wang, Kenli Li, “A System call Learning Atoms Based on Plug away Short-Term Memory Recurrent Neural Networks,” 2018 IEEE International Conference exertion Bioinformatics and Biomedicine (BIBM), 728-733, 2018.