Qin Mao

512 total citations · 1 hit paper
6 papers, 297 citations indexed

About

Qin Mao is a scholar working on Infectious Diseases, Molecular Biology and Surgery. According to data from OpenAlex, Qin Mao has authored 6 papers receiving a total of 297 indexed citations (citations by other indexed papers that have themselves been cited), including 2 papers in Infectious Diseases, 2 papers in Molecular Biology and 1 paper in Surgery. Recurrent topics in Qin Mao's work include COVID-19 Clinical Research Studies (2 papers), SARS-CoV-2 and COVID-19 Research (1 paper) and Influenza Virus Research Studies (1 paper). Qin Mao is often cited by papers focused on COVID-19 Clinical Research Studies (2 papers), SARS-CoV-2 and COVID-19 Research (1 paper) and Influenza Virus Research Studies (1 paper). Qin Mao collaborates with scholars based in China, Japan and United States. Qin Mao's co-authors include Zhanhui Feng, Mingwei Wang, Xiang Zhou, Chen Chen, Jiake Tang, Qi Wu, Wen Wen, Yongran Cheng, Mengyun Zhou and Xingwei Zhang and has published in prestigious journals such as International Journal of Molecular Sciences, Ecotoxicology and Environmental Safety and Redox Biology.

In The Last Decade

Qin Mao

5 papers receiving 293 citations

Hit Papers

Efficacy and safety of three new oral antiviral treatment... 2022 2026 2023 2024 2022 50 100 150 200 250

Peers

Qin Mao
Comparison fields: 5 of 76
  • Infectious Diseases 211
  • Neurology 70
  • Molecular Biology 49
  • Computational Theory and Mathematics 35
  • Epidemiology 34
Replace Ramazan Sabırlı with:
Ramazan Sabırlı Türkiye
Helen Tanner Australia
Jiandan Qian China
Genki Ichihashi Japan
Yuko Tsuge Japan
Volker Thieme Germany
Weiyin Lin China
Xudan Chen China
Jiake Tang China
Alison Boyle United Kingdom
Ramazan Sabırlı Türkiye View profile →
Citations per field, relative to Qin Mao
Qin Mao · 1×
Citations per year, relative to Qin Mao
Qin Mao · 1×

Countries citing papers authored by Qin Mao

Since Specialization
Citations

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

Fields of papers citing papers by Qin Mao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Qin Mao

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

All Works

6 of 6 papers shown
# Work Indexed citations
1 1
2 0
3 1
4 1
5
Efficacy and safety of three new oral antiviral treatment (molnupiravir, fluvoxamine and Paxlovid) for COVID-19:a meta-analysis breakdown →
272
6 22

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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