智慧医疗、免疫信息学与药物发现

1 Wei Qu, Ronghui You, Hiroshi Mamitsuka, Shanfeng Zhu*, DeepMHCI: an anchor position-aware deep interaction model for accurate MHC-I peptide binding affinity prediction, Bioinformatics, 39(9):btad551 (2023)

2 Weiqi Zhai, Xiaodi Huang, Nan Shen, Shanfeng Zhu*, Phen2Disease: a phenotype-driven model for disease and gene prioritization by bidirectional maximum matching semantic similarities, Briefings in Bioinformatics, 24(4):bbad172 (2023)

3 Zhirui Liao, Lei Xie, Hiroshi Mamitsuka, Shanfeng Zhu*, Sc2Mol: a scaffold-based two-step molecule generator with variational autoencoder and transformer, Bioinformatics, 39 (1): btac814, (2023)

4 Ronghui You, Wei Qu, Hiroshi Mamitsuka, Shanfeng Zhu*, DeepMHCII: A Novel Binding Core-Aware Deep Interaction Model for Accurate MHC II-peptide Binding Affinity Prediction. Bioinformatics(ISMB2022), 38(S1), i220-i228 (2022)

5 Jing Yan # , Weiqi Zhai # , Zhaoxia Li, LingLing Ding, Jia You, Jiayi Zeng, Xin Yang, Chunjuan Wang, Xia Meng, Yong Jiang, Xiaodi Huang, Shouyan Wang, Yilong Wang, Zixiao Li(*), Shanfeng Zhu(*), Yongjun Wang, Xingquan Zhao(*), Jianfeng Feng. ICH-LR2S2: a new risk score for predicting stroke-associated pneumonia from spontaneous intracerebral hemorrhage. J Transl Med. 20(1):193, (2022)

6 Lizhi Liu, Hiroshi Mamitsuka, Shanfeng Zhu*, HPODNets: deep graph convolutional networks for predicting human protein-phenotype associations, Bioinformatics, 38 (3): 799-808, (2022)

7 Lizhi Liu, Xiaodi Huang, Hiroshi Mamitsuka, Shanfeng Zhu*, HPOFiller: Identifying Missing Protein-phenotype Associations by Graph Convolutional Network. Bioinformatics, 37 (19), 3328–3336, (2021)

8 Lizhi Liu, Xiaodi Huang, Hiroshi Mamitsuka, Shanfeng Zhu*, HPOLabeler: Improving prediction of human protein-phenotype associations by learning to rank. Bioinformatics 36(14)4180-4188(2020)

9 Qingjun Yuan, Junning Gao, Dongliang Wu, Shihua Zhang, Hiroshi Mamitsuka, Shanfeng Zhu*, DrugE-Rank: improving drug–target interaction prediction of new candidate drugs or targets by ensemble learning to rank. Bioinformatics(ISMB2016)，2016 32(12). i18-27

10 Xiaodong Zheng, Hao Ding, Hiroshi Mamitsuka, Shanfeng Zhu. Collaborative matrix factorization with multiple similarities for predicting drug-target interactions. KDD 2013: 1025-1033

宏基因组

11 Ziye Wang, Ronghui You, Haitao Han, Wei Liu, Fengzhu Sun, Shanfeng Zhu*, Effective binning of metagenomic contigs using contrastive multi-view representation learning. Nature Communications. 2024;15(1):585

12 Ziye Wang, Pingqing Huang, Ronghui You, Fengzhu Sun, Shanfeng Zhu*, MetaBinner: a high-performance and stand-alone ensemble binning method to recover individual genomes from complex microbial communities, Genome Biology, 24(1):1.(2023) (First Place in Contig Binning in CAMI II)

13 Ziye Wang, Zhengyang Wang, Yang Young Lu, Fengzhu Sun*, Shanfeng Zhu* SolidBin: improving metagenome binning with semi-supervised normalized cut. Bioinformatics 35(21): 4229-4238(2019)

蛋白序列、结构与功能

14 Wei Liu, Ziye Wang, Ronghui You, Chenghan Xie, Hong Wei，Yi Xiong, Jianyi Yang*, Shanfeng Zhu*. PLMSearch: Protein language model powers accurate and fast sequence search for remote homology. Nature Communications. 2024;15(1):2775.

15 Shaojun Wang, Ronghui You, Yunjia Liu, Yi Xiong, Shanfeng Zhu*, NetGO 3.0: Protein Language Model Improves Large-scale Functional Annotations, Genomics, Proteomics & Bioinformatics, 21(2):349-358（2023）（First Place in CAFA5）

16 Ronghui You, Shuwei Yao, Hiroshi Mamitsuka, Shanfeng Zhu*, DeepGraphGO: graph neural network for large-scale, multispecies protein function prediction. Bioinformatics (ISMB/ECCB2021), 37(S1) i262-i271

17 Shuwei Yao, Ronghui You, Shaojun Wang, Yi Xiong, Xiaodi Huang, Shanfeng Zhu*. NetGO 2.0: improving large-scale protein function prediction with massive sequence, text, domain, family and network information. Nucleic Acids Res. 49(W1):W469-475 (2021) （First Place in CAFA4）

18 Ronghui You, Shuwei Yao, Yi Xiong, Xiaodi Huang, Fengzhu Sun, Hiroshi Mamituska, Shanfeng Zhu*, NetGO: improving large-scale protein function prediction with massive network information. Nucleic Acids Research,47(W1),W379–W387(2019)

19 Ronghui You, Zhihan Zhang, Yi Xiong, Fengzhu Sun, Hiroshi Mamitsuka, Shanfeng Zhu* GOLabeler: Improving Sequence-based Large-scale Protein Function Prediction by Learning to Rank. Bioinformatics 34(14)2465-2473,(2018) （First Place in CAFA3）

信息检索、文本挖掘与机器学习

20 Junyi Bian, Li Huang, Xiaodi Huang, Hong Zhou and Shanfeng Zhu*. GrantRel: Grant Information Extraction via Joint Entity and Relation Extraction. Findings of ACL2021, 2674-2685

21 Ronghui You, Yuxuan Liu, Hiroshi Mamitsuka, Shanfeng Zhu*. BERTMeSH: deep contextual representation learning for large-scale high-performance MeSH indexing with full text. Bioinformatics, 37(5): 684-692 (2021)

22 Suyang Dai, Ronghui You, Zhiyong Lu, Xiaodi Huang, Hiroshi Mamitsuka, Shanfeng Zhu*: FullMeSH: improving large-scale MeSH indexing with full text. Bioinformatics. 36(5): 1533-1541(2020)

23 Ronghui You, Zihan Zhang, Ziye Wang, Suyang Dai, Hiroshi Mamitsuka, Shanfeng Zhu*: AttentionXML: Label Tree-based Attention-Aware Deep Model for High-Performance Extreme Multi-Label Text Classification. NeurIPS 2019: 5812-5822(2019)(First Place of BioASQ 10，9a, 8a and 7a)

24 Shengwen Peng, Ronghi You, Hongning Wang, Hiroshi Mamitsuka, Shanfeng Zhu*, DeepMeSH: Deep Semantic Representation for Improving Large-scale MeSH Indexing. Bioinformatics(ISMB2016), 2016，32(12) i70-79(First Place of BioASQ 5a and 4a)

25 Ke Liu, Shengwen Peng, Junqiu Wu, Chengxiang Zhai, Hiroshi Mamitsuka, Shanfeng Zhu*, MeSHLabeler: Improving the Accuracy of large-scale MeSH indexing by Integrating Diverse Evidence. Bioinformatics(ISMB2015), 2015, 31(12): i339-i347(First Place of BioASQ 3a and 2a)

26 Junning Gao, Makoto Yamada, Samuel Kaski, Hiroshi Mamitsuka, Shanfeng Zhu*, A Robust Convex Formulation for Ensemble Clustering. Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI 2016),New York,USA Jul. 2015,AAAI Press,1476-1482

27 Xiaodong Zheng, Shanfeng Zhu*, Junning Gao, Hiroshi Mamitsuka, Instance-wise Weighted Nonnegative Matrix Factorization for Aggregating Partitions with Locally Reliable Clusters. Proceedings of the 24th International Joint Conference on Artificial Intelligence(IJCAI 2015),Buenos Aires, Argentina Jul. 2015, AAAI Press,4091-4097.