Mingyu Gan

1.5k citations
25 papers · 776 · h-index 13

Impact in

    • Tuberculosis Research and Epidemiology
    • Mycobacterium research and diagnosis
    • Pneumocystis jirovecii pneumonia detection and treatment
    • Pneumonia and Respiratory Infections

Papers in

    • Mycobacterium research and diagnosis 15
    • Pneumocystis jirovecii pneumonia detection and treatment 4
    • Pneumonia and Respiratory Infections 2
    • Tuberculosis Research and Epidemiology 15

Mingyu Gan

24 papers receiving 772 citations

Peers

Mingyu Gan
Comparison fields: 5 of 68
  • Infectious Diseases 646
  • Epidemiology 649
  • Molecular Medicine 55
  • Surgery 261
  • Clinical Biochemistry 25
Replace Marta Herránz with:
Marta Herránz Spain
Olga Ignatyeva Russia
Irina Kontsevaya United Kingdom
Mark D. Leney United States
Themba Mzembe United Kingdom
Elis Regina Dalla Costa Brazil
T. C. Victor South Africa
Elias N. Ntinginya Germany
Mahmud Hanif India
Soudeh Ehsani United Kingdom
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Citations per field
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Marta Herránz · 1×
Citations per year

Countries citing papers authored by Mingyu Gan

Since Specialization
Citations

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

Fields of papers citing papers by Mingyu Gan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Mingyu Gan, 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 Mingyu Gan Line = papers co-authored together Mingyu Gan links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016189
2 2015117
3 201880
4 201878
5 202239
6 201735
7 201633
8 202131
9 202129
10 201829
11 202127
12 202321
13 201716
14 202110
15 20249
16 20218
17 20246
18 20225
19 20244
20 20243

About Mingyu Gan

Mingyu Gan is a scholar working on Epidemiology, Infectious Diseases, Molecular Biology, Surgery and Genetics, having authored 25 papers that have together received 776 indexed citations. Recurring topics across this work include Tuberculosis Research and Epidemiology (15 papers), Mycobacterium research and diagnosis (15 papers), Pneumocystis jirovecii pneumonia detection and treatment (4 papers), Genomics and Phylogenetic Studies (3 papers), Neonatal and Maternal Infections (2 papers), Infectious Diseases and Tuberculosis (2 papers), RNA and protein synthesis mechanisms (2 papers) and Pneumonia and Respiratory Infections (2 papers). The work is most often cited by research in Infectious Diseases (646 citations), Epidemiology (649 citations), Molecular Medicine (55 citations), Surgery (261 citations) and Clinical Biochemistry (25 citations). Mingyu Gan has collaborated with scholars based in China, United States and Venezuela. Frequent co-authors include Qingyun Liu, Qian Gao, Chongguang Yang, Tāo Luò, Xin Shen, Jian Mei, Kathryn DeRiemer, Tianyu Zuo, Jie Wu and Peng Xu. Their work appears in journals such as Proceedings of the National Academy of Sciences, Tuberculosis, The Lancet Infectious Diseases, The Journal of Infectious Diseases and Scientific Reports.

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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