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  • Shanfeng ZHU
  • Research Direction:Artificial Intelligence and Big Biomedical Data Mining Machine Learning and Text Mining
  • Email:zhusf@fudan.edu.cnzhusf@fudan.edu.cn
  • Website:http://datamining-iip.fudan.edu.cn
  • Brief Introduction:Shanfeng Zhu is a Professor at the Institute for Science and Technology for Brain-Inspired Intelligence at Fudan University. He is also a member of Shanghai Key Lab of Intelligent Information Processing, and Key Lab of Computational Neuroscience and Brain-Inspired Intelligence (MOE) at Fudan University. He received his Bachelor and Master degrees in Computer Science at Wuhan University and Ph.D. in Computer Science at City University of Hong Kong in 1996, 1999 and 2003, respectively. Before joining Fudan University in 2008, he was a Postdoctoral Fellow at Bioinformatics Center, Kyoto University. He was a visiting scholar at UIUC (March 2013-March 2014), and a visiting Associate Professor at Kyoto University (July 2016-Nov 2016). He was invited to join UniProt Scientific Advisory Board in Sep 2018. His research focuses on developing and applying machine learning and data mining methods for Bioinformatics and Biomedical Informatics, especially biomedical text mining, protein function prediction, immunological informatics, drug discovery and Metagenomics.
  • Achievement:

    Immunoinformatic,DrugDiscoveryand Precision Medicine

    1.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)

    2.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

    3.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, ZixiaoLi(*), 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)

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

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

    6.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)

    7.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

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


    9.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)

    10.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)

    Protein Sequence, Structure and Function

    11.ShaojunWang,Ronghui You, Yunjia Liu, Yi Xiong, Shanfeng Zhu*, NetGO 3.0: Protein Language Model Improves Large-scale Functional Annotations, Genomics, Proteomics & Bioinformatics, In Press

    12.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

    13.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)

    14.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)

    15.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)

    Information Retrieval, Text Mining and Machine Learning

    16.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

    17.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)

    18.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)

    19.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)

    20.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)

    21.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)

    22.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

    23.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.