Yang Fu

6.4k total citations · 1 hit paper
67 papers, 2.0k citations indexed

About

Yang Fu is a scholar working on Molecular Biology, Immunology and Genetics. According to data from OpenAlex, Yang Fu has authored 67 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Molecular Biology, 16 papers in Immunology and 14 papers in Genetics. Recurrent topics in Yang Fu's work include Vibrio bacteria research studies (11 papers), Antibiotic Resistance in Bacteria (11 papers) and Bacterial Genetics and Biotechnology (8 papers). Yang Fu is often cited by papers focused on Vibrio bacteria research studies (11 papers), Antibiotic Resistance in Bacteria (11 papers) and Bacterial Genetics and Biotechnology (8 papers). Yang Fu collaborates with scholars based in China, United States and United Kingdom. Yang Fu's co-authors include John J. Mekalanos, Matthew K. Waldor, Emrah Altındiş, Jun Chen, Hong Yu, Lei Liu, Zhibin Zhu, Pengcheng Ou, Qing He and Zhiwei Li and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Journal of Biological Chemistry.

In The Last Decade

Yang Fu

64 papers receiving 2.0k citations

Hit Papers

COVID‐19 in a designated infectious diseases hospital out... 2020 2026 2022 2024 2020 100 200 300

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Yang Fu China 25 692 585 435 303 245 67 2.0k
Sandeep Tiwari Brazil 20 777 1.1× 451 0.8× 174 0.4× 91 0.3× 108 0.4× 74 1.6k
Xiaoling Ma China 30 1.6k 2.2× 926 1.6× 125 0.3× 189 0.6× 462 1.9× 116 3.3k
Huahao Fan China 24 698 1.0× 877 1.5× 141 0.3× 85 0.3× 121 0.5× 114 2.2k
Yi‐Han Lin United States 15 685 1.0× 339 0.6× 154 0.4× 163 0.5× 83 0.3× 40 1.3k
Kok‐Fai Kong United States 19 1.0k 1.5× 416 0.7× 192 0.4× 150 0.5× 425 1.7× 25 2.1k
Helena Thomaides‐Brears United Kingdom 18 607 0.9× 296 0.5× 154 0.4× 474 1.6× 93 0.4× 35 1.4k
Peng Cui China 37 1.4k 2.0× 859 1.5× 123 0.3× 263 0.9× 251 1.0× 112 3.6k
Toshinobu Horii Japan 24 763 1.1× 497 0.8× 370 0.9× 191 0.6× 856 3.5× 80 2.1k
Xu Jia China 19 407 0.6× 632 1.1× 153 0.4× 65 0.2× 355 1.4× 50 1.7k
Antonio DiGiandomenico United States 26 997 1.4× 325 0.6× 283 0.7× 193 0.6× 533 2.2× 50 2.1k

Countries citing papers authored by Yang Fu

Since Specialization
Citations

This map shows the geographic impact of Yang Fu's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Yang Fu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yang Fu more than expected).

Fields of papers citing papers by Yang Fu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yang Fu. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Yang Fu. The network helps show where Yang Fu may publish in the future.

Co-authorship network of co-authors of Yang Fu

This figure shows the co-authorship network connecting the top 25 collaborators of Yang Fu. A scholar is included among the top collaborators of Yang Fu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Yang Fu. Yang Fu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
2.
Long, Yanping, et al.. (2025). De novo non-canonical nanopore basecalling enables private communication using heavily-modified DNA data at single-molecule level. Nature Communications. 16(1). 4099–4099. 1 indexed citations
3.
Liu, Ming, Heng Wang, Zhao Wang, et al.. (2025). A Vibrio-specific T6SS effector reshapes microbial competition by disrupting Vibrio bioenergetics. Cell Host & Microbe. 33(7). 1146–1160.e8.
4.
Hu, Xiaohui, Yuting Zhang, Lijie Wu, et al.. (2023). A potent neutralizing nanobody targeting a unique epitope on the receptor-binding domain of SARS-CoV-2 spike protein. Virology. 589. 109925–109925. 3 indexed citations
5.
Pei, Tong‐Tong, et al.. (2022). Abiotic factors modulate interspecies competition mediated by the type VI secretion system effectors in Vibrio cholerae. The ISME Journal. 16(7). 1765–1775. 19 indexed citations
7.
Zhang, Kuo, Ting Peng, Miao Tian, et al.. (2022). Structural insights into caspase ADPR deacylization catalyzed by a bacterial effector and host calmodulin. Molecular Cell. 82(24). 4712–4726.e7. 7 indexed citations
8.
Bao, Wuping, Xue Zhang, Yang Fu, et al.. (2021). Factors Associated with the Expression of ACE2 in Human Lung Tissue: Pathological Evidence from Patients with Normal FEV1 and FEV1/FVC. Journal of Inflammation Research. Volume 14. 1677–1687. 10 indexed citations
9.
Bao, Wuping, Xue Tian, Xueqian Xie, et al.. (2021). Is small airway dysfunction an abnormal phenomenon for patients with normal forced expiratory volume in 1 second and the ratio of forced expiratory volume in 1 second to forced vital capacity?. Annals of Allergy Asthma & Immunology. 128(1). 68–77.e1. 9 indexed citations
10.
Chen, Lu, Jian‐Wen Sun, Yang Fu, et al.. (2021). Structure-guided discovery of potent and oral soluble epoxide hydrolase inhibitors for the treatment of neuropathic pain. Acta Pharmaceutica Sinica B. 12(3). 1377–1389. 9 indexed citations
11.
Fu, Yang, Li Zhu, Li Zhou, et al.. (2021). The Multiple Regulatory Relationship Between RNA-Chaperone Hfq and the Second Messenger c-di-GMP. Frontiers in Microbiology. 12. 689619–689619. 10 indexed citations
12.
Cai, Qingxian, Deliang Huang, Pengcheng Ou, et al.. (2020). COVID‐19 in a designated infectious diseases hospital outside Hubei Province, China. Allergy. 75(7). 1742–1752. 372 indexed citations breakdown →
13.
Li, Jian, Yan Zhang, Peter J. McCormick, et al.. (2020). Crystal structure of SARS-CoV-2 main protease in complex with the natural product inhibitor shikonin illuminates a unique binding mode. Science Bulletin. 66(7). 661–663. 49 indexed citations
14.
Fu, Yang, Brian T. Ho, & John J. Mekalanos. (2018). Tracking Vibrio cholerae Cell-Cell Interactions during Infection Reveals Bacterial Population Dynamics within Intestinal Microenvironments. Cell Host & Microbe. 23(2). 274–281.e2. 40 indexed citations
15.
Fu, Yang, et al.. (2018). c-di-GMP Regulates Various Phenotypes and Insecticidal Activity of Gram-Positive Bacillus thuringiensis. Frontiers in Microbiology. 9. 45–45. 31 indexed citations
16.
Wu, Daichao, Lingzhi Qu, Yang Fu, et al.. (2016). Expression and purification of the kinase domain of PINK1 in Pichia pastoris. Protein Expression and Purification. 128. 67–72. 4 indexed citations
17.
Tang, Qing, Kang Yin, Hongliang Qian, et al.. (2016). Cyclic di-GMP contributes to adaption and virulence of Bacillus thuringiensis through a riboswitch-regulated collagen adhesion protein. Scientific Reports. 6(1). 28807–28807. 29 indexed citations
18.
Babina, Arianne M., et al.. (2015). An S6:S18 complex inhibits translation of E. coli rpsF. RNA. 21(12). 2039–2046. 14 indexed citations
19.
Fu, Yang, et al.. (2013). Bacterial RNA motif in the 5′ UTR of rpsF interacts with an S6:S18 complex. RNA. 20(2). 168–176. 17 indexed citations
20.
Shi, Lijia, Gang Yan, Yang Fu, et al.. (1997). Human TAP1 polymorphisms detected by denaturing gradient gel electrophoresis. Tissue Antigens. 49(4). 421–426. 10 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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