Yan Wu

9.3k total citations · 2 hit papers
105 papers, 3.9k citations indexed

About

Yan Wu is a scholar working on Molecular Biology, Epidemiology and Infectious Diseases. According to data from OpenAlex, Yan Wu has authored 105 papers receiving a total of 3.9k indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Molecular Biology, 33 papers in Epidemiology and 30 papers in Infectious Diseases. Recurrent topics in Yan Wu's work include SARS-CoV-2 and COVID-19 Research (16 papers), Influenza Virus Research Studies (15 papers) and Respiratory viral infections research (10 papers). Yan Wu is often cited by papers focused on SARS-CoV-2 and COVID-19 Research (16 papers), Influenza Virus Research Studies (15 papers) and Respiratory viral infections research (10 papers). Yan Wu collaborates with scholars based in China, United States and Japan. Yan Wu's co-authors include George F. Gao, Yi Shi, Scott Stawicki, Jianxun Qi, Marc Tessier‐Lavigne, Jasvinder K. Atwal, Carla J. Shatz, Ying Wu, Boris Tefsen and Cecilia Chiu and has published in prestigious journals such as Nature, Science and Proceedings of the National Academy of Sciences.

In The Last Decade

Yan Wu

100 papers receiving 3.8k citations

Hit Papers

Both Boceprevir and GC376 efficaciously inhibit SARS-CoV-... 2020 2026 2022 2024 2020 2020 100 200 300

Peers

Yan Wu
Comparison fields: 5 of 132
  • Molecular Biology 1.5k
  • Epidemiology 1.0k
  • Infectious Diseases 983
  • Immunology 618
  • Cellular and Molecular Neuroscience 446
Thottethodi Subrahmanya Keshava Prasad India
Sheng Li United States
Licia Tomei Italy
Tomozumi Imamichi United States
Yves Rouillé France
Tuula A. Nyman Finland
Susumu Kawamoto Japan
Massimo Santoro Italy
Hassan Y. Naim Germany
Maojun Yang China
Thottethodi Subrahmanya Keshava Prasad India View profile →
Citations per field, relative to Yan Wu
Yan Wu · 1×
Citations per year, relative to Yan Wu
Yan Wu · 1×

Countries citing papers authored by Yan Wu

Since Specialization
Citations

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

Fields of papers citing papers by Yan Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yan Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Yan Wu. A scholar is included among the top collaborators of Yan 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 Yan Wu. Yan 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 1
2 3
3 0
4 12
5 12
6 0
7 1
8 6
9 26
10 12
11 10
12 22
13 1
14 22
15 10
16 8
17
Both Boceprevir and GC376 efficaciously inhibit SARS-CoV-2 by targeting its main protease breakdown →
392
18 8
19 2
20 77

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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