Bin Tan

531 citations
13 papers · 345 · 1 hit paper · h-index 8

Impact in

Papers in

    • SARS-CoV-2 and COVID-19 Research 7
    • Viral gastroenteritis research and epidemiology 2
    • SARS-CoV-2 detection and testing 1
    • RNA and protein synthesis mechanisms 2
    • RNA Interference and Gene Delivery 2
    • Ion channel regulation and function 1

Bin Tan

12 papers receiving 340 citations

Bin Tan's Hit Papers

Design of a SARS-CoV-2 papain-like protease inhibitor with antiviral efficacy in a mouse model 2024 · 53 citations
530+1Years since publication1020304050

Peers

Bin Tan
Comparison fields: 5 of 50
  • Infectious Diseases 153
  • Computational Theory and Mathematics 138
  • Organic Chemistry 99
  • Molecular Biology 111
  • Pharmacology 11
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Yinkai Duan China
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Maura V. Gongora United States
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Bin Tan relative to Scott J. Barraza United States Scott J. Barraza's profile →
Citations per field
00.5×2×4×6×8×
Scott J. Barraza · 1×
Citations per year

Countries citing papers authored by Bin Tan

Since Specialization
Citations

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

Fields of papers citing papers by Bin Tan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Bin Tan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Bin Tan Line = papers co-authored together Bin Tan links everyone, so they are left out of the graph.

All Works

13 of 13 papers shown
#Work
1 2022104
2 202269
3
Design of a SARS-CoV-2 papain-like protease inhibitor with antiviral efficacy in a mouse model
Hit paper breakdown →
202453
4 202238
5 202319
6 202015
7 202314
8 202513
9 20236
10 20246
11 20085
12 20223
13 20250

About Bin Tan

Bin Tan is a scholar working on Infectious Diseases, Molecular Biology, Cardiology and Cardiovascular Medicine, Computational Theory and Mathematics and Organic Chemistry, having authored 13 papers that have together received 345 indexed citations. Recurring topics across this work include SARS-CoV-2 and COVID-19 Research (7 papers), Viral Infections and Immunology Research (4 papers), Computational Drug Discovery Methods (4 papers), RNA and protein synthesis mechanisms (2 papers), RNA Interference and Gene Delivery (2 papers), Viral gastroenteritis research and epidemiology (2 papers), SARS-CoV-2 detection and testing (1 paper) and Ion channel regulation and function (1 paper). The work is most often cited by research in Infectious Diseases (153 citations), Computational Theory and Mathematics (138 citations), Organic Chemistry (99 citations), Molecular Biology (111 citations) and Pharmacology (11 citations). Bin Tan has collaborated with scholars based in United States, China and Greece. Frequent co-authors include Jun Wang, Haozhou Tan, Yanmei Hu, Prakash D. Jadhav, Kan Li, Xufang Deng, Eddy Arnold, Francesc X. Ruiz, Yuye Chen and Yuyang Jiang. Their work appears in journals such as Journal of Medicinal Chemistry, European Journal of Medicinal Chemistry, Nature Communications, ACS Chemical Neuroscience and Bioorganic & Medicinal Chemistry Letters.

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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