Shanfeng Zhu

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Ronghui YouFudan UniversityVerified email at fudan.edu.cn
Xiaodi HuangCharles Sturt University, AustraliaVerified email at csu.edu.au
Fengzhu SunUniversity of Southern CaliforniaVerified email at usc.edu
Xiaotie DengChair Professor of Computer Science, Peking University, Beijing, ChinaVerified email at pku.edu.cn
Ziye WangFudan UniversityVerified email at fudan.edu.cn
Yi XiongShanghai Jiao Tong UniversityVerified email at sjtu.edu.cn
Ichigaku TakigawaKyoto University / Hokkaido UniversityVerified email at kyoto-u.ac.jp
ChengXiang ZhaiUniversity of Illinois at Urbana-ChampaignVerified email at illinois.edu
Lizhi LiuSchool of Computer Science, Fudan UniversityVerified email at fudan.edu.cn
Yanchun ZhangZhejiang Normal University，Victoria UniversityVerified email at vu.edu.au
Haoran XieHead & Associate Professor, Lingnan University, Hong KongVerified email at ln.edu.hk
Xihao HuGV20 TherapeuticsVerified email at gv20therapeutics.com
Feng WangAssociate Professor, Wuhan UniversityVerified email at whu.edu.cn
Hong YanCity University of Hong KongVerified email at cityu.edu.hk
Shihua ZhangProfessor of Academy of Mathematics and Systems Science, Chinese Academy of SciencesVerified email at amss.ac.cn
Hau-San WongProfessor, Department of Computer Science, City University of Hong KongVerified email at cityu.edu.hk
Shuigeng ZhouFudan UniversityVerified email at fudan.edu.cn
Hongning WangAssociate Professor, Department of Computer Science, University of VirginiaVerified email at virginia.edu
Claus LundegaardDirector, ZS Associates, DiscoveryVerified email at zs.com
Qing LiChair Professor (Data Science), the Hong Kong Polytechnic UniversityVerified email at comp.polyu.edu.hk

Shanfeng Zhu

Professor, Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University

Verified email at fudan.edu.cn - Homepage

Bioinformatics AI Biomedical Big Data Machine Learning Text Mining


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Similarity-based machine learning methods for predicting drug–target interactions: a brief review H Ding, I Takigawa, H Mamitsuka, S Zhu Briefings in bioinformatics 15 (5), 734-747, 2014	433	2014
Collaborative matrix factorization with multiple similarities for predicting drug-target interactions X Zheng, H Ding, H Mamitsuka, S Zhu Proceedings of the 19th ACM SIGKDD international conference on Knowledge …, 2013	360	2013
The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens N Zhou, Y Jiang, TR Bergquist, AJ Lee, BZ Kacsoh, AW Crocker, ... Genome biology 20 (1), 1-23, 2019	350	2019
Attentionxml: Label tree-based attention-aware deep model for high-performance extreme multi-label text classification R You, Z Zhang, Z Wang, S Dai, H Mamitsuka, S Zhu NeurIPS 2019, 5812-5822, 2019	268	2019
Critical Assessment of Metagenome Interpretation: the second round of challenges F Meyer, A Fritz, ZL Deng, D Koslicki, TR Lesker, A Gurevich, G Robertson, ... Nature methods 19 (4), 429-440, 2022	189	2022
GOLabeler: improving sequence-based large-scale protein function prediction by learning to rank R You, Z Zhang, Y Xiong, F Sun, H Mamitsuka, S Zhu Bioinformatics 34 (14), 2465-2473, 2018	156	2018
Toward more accurate pan-specific MHC-peptide binding prediction: a review of current methods and tools L Zhang, K Udaka, H Mamitsuka, S Zhu Briefings in bioinformatics 13 (3), 350-364, 2012	154	2012
DrugE-Rank: improving drug–target interaction prediction of new candidate drugs or targets by ensemble learning to rank Q Yuan, J Gao, D Wu, S Zhang, H Mamitsuka, S Zhu Bioinformatics 32 (12), i18-i27, 2016	130	2016
TEPITOPEpan: extending TEPITOPE for peptide binding prediction covering over 700 HLA-DR molecules L Zhang, Y Chen, HS Wong, S Zhou, H Mamitsuka, S Zhu PLoS One 7 (2), e30483, 2012	130	2012
A probabilistic model for mining implicit ‘chemical compound–gene’relations from literature S Zhu, Y Okuno, G Tsujimoto, H Mamitsuka Bioinformatics 21 (suppl_2), ii245-ii251, 2005	129	2005
DeepMeSH: deep semantic representation for improving large-scale MeSH indexing S Peng, R You, H Wang, C Zhai, H Mamitsuka, S Zhu Bioinformatics 32 (12), i70-i79, 2016	128	2016
Enhancing MEDLINE document clustering by incorporating MeSH semantic similarity S Zhu, J Zeng, H Mamitsuka Bioinformatics 25 (15), 1944-1951, 2009	115	2009
NetGO: improving large-scale protein function prediction with massive network information R You, S Yao, Y Xiong, X Huang, F Sun, H Mamitsuka, S Zhu Nucleic acids research 47 (W1), W379-W387, 2019	107	2019
Crowdsourced estimation of cognitive decline and resilience in Alzheimer's disease GI Allen, N Amoroso, C Anghel, V Balagurusamy, CJ Bare, D Beaton, ... Alzheimer's & Dementia 12 (6), 645-653, 2016	88	2016
Does summarization help stock prediction? A news impact analysis X Li, H Xie, Y Song, S Zhu, Q Li, FL Wang IEEE intelligent systems 30 (3), 26-34, 2015	81	2015
MeSHLabeler: improving the accuracy of large-scale MeSH indexing by integrating diverse evidence K Liu, S Peng, J Wu, C Zhai, H Mamitsuka, S Zhu Bioinformatics 31 (12), i339-i347, 2015	80	2015
Enhancing quantitative intra-day stock return prediction by integrating both market news and stock prices information X Li, X Huang, X Deng, S Zhu Neurocomputing 142, 228-238, 2014	79	2014
DeepText2Go: Improving large-scale protein function prediction with deep semantic text representation R You, X Huang, S Zhu Methods 145, 82-90, 2018	74	2018
Towards accurate human promoter recognition: a review of currently used sequence features and classification methods J Zeng, S Zhu, H Yan Briefings in bioinformatics 10 (5), 498-508, 2009	72	2009
Improving stock market prediction by integrating both market news and stock prices X Li, C Wang, J Dong, F Wang, X Deng, S Zhu International Conference on Database and Expert Systems Applications, 279-293, 2011	71	2011

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