Yinkai Duan

6.9k citations
7 papers · 459 indexed · 1 hit paper · h-index 5
Topics
SARS-CoV-2 and COVID-19 Research (7 papers)Computational Drug Discovery Methods (4 papers)COVID-19 Clinical Research Studies (3 papers)

In The Last Decade

Yinkai Duan

7 papers receiving 456 citations

Hit Papers

Multiple pathways for SARS-CoV-2 resistance to nirmatrelvir2022202620232024202250100150200250

Peers

Yinkai Duan
Comparison fields: 5 of 64
  • Infectious Diseases 318
  • Computational Theory and Mathematics 202
  • Molecular Biology 155
  • Organic Chemistry 58
  • Immunology 35
Replace Maura V. Gongora with:
Maura V. Gongora United States
M.M. Kashipathy United States
Jesús Urquiza Spain
Kristina Lanko Netherlands
Chuanjuan Tao United States
Carina Stiller Germany
Haozhou Tan United States
Krishani Dinali Perera United States
Wayne Vuong Canada
Soo Young Byun South Korea
Yinkai Duan relative to Maura V. Gongora United States Maura V. Gongora's profile →
Citations per field
00.5×1.5×
Maura V. Gongora · 1×
Citations per year

Countries citing papers authored by Yinkai Duan

Since Specialization
Citations

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

Fields of papers citing papers by Yinkai Duan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yinkai Duan

This figure shows the co-authorship network connecting the top 25 collaborators of Yinkai Duan. A scholar is included among the top collaborators of Yinkai Duan 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 Yinkai Duan. Yinkai Duan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

7 of 7 papers shown
#WorkIndexed citations
1 1
2 3
3 32
4 24
5 106
6
Multiple pathways for SARS-CoV-2 resistance to nirmatrelvirbreakdown →
260
7 33

About Yinkai Duan

Yinkai Duan is a scholar working on Infectious Diseases, Computational Theory and Mathematics and Radiology, Nuclear Medicine and Imaging, having authored 7 papers that have together received 459 indexed citations. Recurring topics across this work include SARS-CoV-2 and COVID-19 Research (7 papers), Computational Drug Discovery Methods (4 papers) and COVID-19 Clinical Research Studies (3 papers). The work is most often cited by research in Infectious Diseases (318 citations), Computational Theory and Mathematics (202 citations) and Molecular Biology (155 citations). Yinkai Duan has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Haitao Yang, Yicheng Guo, Alejandro Chavez, Zizhang Sheng, Anne‐Catrin Uhlemann, Bruce Culbertson, Seo Jung Hong, Sho Iketani, Stephen P. Goff and Yosef Sabo. Their work appears in journals such as Nature, Proceedings of the National Academy of Sciences and Nature Communications.

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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