Yanling Wu

5.3k total citations · 2 hit papers
64 papers, 2.9k citations indexed

About

Yanling Wu is a scholar working on Infectious Diseases, Radiology, Nuclear Medicine and Imaging and Molecular Biology. According to data from OpenAlex, Yanling Wu has authored 64 papers receiving a total of 2.9k indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Infectious Diseases, 22 papers in Radiology, Nuclear Medicine and Imaging and 18 papers in Molecular Biology. Recurrent topics in Yanling Wu's work include Monoclonal and Polyclonal Antibodies Research (22 papers), SARS-CoV-2 and COVID-19 Research (16 papers) and Immune Cell Function and Interaction (10 papers). Yanling Wu is often cited by papers focused on Monoclonal and Polyclonal Antibodies Research (22 papers), SARS-CoV-2 and COVID-19 Research (16 papers) and Immune Cell Function and Interaction (10 papers). Yanling Wu collaborates with scholars based in China, United States and Japan. Yanling Wu's co-authors include Tianlei Ying, Shibo Jiang, Lu Lu, Shuai Xia, Zheng‐Li Shi, Zhenlin Yang, Xiaolong Tian, Ailing Huang, Cheng Li and Annoor Awadasseid and has published in prestigious journals such as Journal of the American Chemical Society, Nature Communications and SHILAP Revista de lepidopterología.

In The Last Decade

Yanling Wu

57 papers receiving 2.8k citations

Hit Papers

Potent binding of 2019 novel coronavirus spike protein by... 2020 2026 2022 2024 2020 2020 250 500 750

Peers

Yanling Wu
Comparison fields: 5 of 125
  • Infectious Diseases 2.0k
  • Molecular Biology 775
  • Radiology, Nuclear Medicine and Imaging 481
  • Immunology 378
  • Biomedical Engineering 252
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Yongfei Cai United States
Jian Yu United States
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Rita E. Chen United States
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Shuai Xia China
Fei Yu China
Emma C. Thomson United Kingdom
Alessandro M. Carabelli United Kingdom View profile →
Citations per field, relative to Yanling Wu
Yanling Wu · 1×
Citations per year, relative to Yanling Wu
Yanling Wu · 1×

Countries citing papers authored by Yanling Wu

Since Specialization
Citations

This map shows the geographic impact of Yanling Wu'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 Yanling Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yanling Wu more than expected).

Fields of papers citing papers by Yanling Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yanling Wu. 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 Yanling Wu. The network helps show where Yanling Wu may publish in the future.

Co-authorship network of co-authors of Yanling Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Yanling Wu. A scholar is included among the top collaborators of Yanling Wu 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 Yanling Wu. Yanling Wu 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
# Work Indexed citations
1 2
2 0
3 0
4 12
5 12
6 13
7 6
8 64
9 96
10 0
11 36
12
Potent binding of 2019 novel coronavirus spike protein by a SARS coronavirus-specific human monoclonal antibody breakdown →
838
13 113
14
Fusion mechanism of 2019-nCoV and fusion inhibitors targeting HR1 domain in spike protein breakdown →
518
15 140
16 38
17 181
18 29
19 79
20 2

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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