Mingda Hu

439 citations
32 papers · 313 · h-index 10

Impact in

Papers in

    • Viral gastroenteritis research and epidemiology 5
    • SARS-CoV-2 and COVID-19 Research 4
    • Influenza Virus Research Studies 8

Mingda Hu

29 papers receiving 305 citations

Peers

Mingda Hu
Comparison fields: 5 of 66
  • Endocrinology 33
  • Agronomy and Crop Science 60
  • Infectious Diseases 78
  • Epidemiology 124
  • Molecular Medicine 13
Replace Deyvid Amgarten with:
Deyvid Amgarten Brazil
Ha Minh Lam Vietnam
Sreyngim Lay United States
Iwona Dąbrowska Poland
Xinna Li China
Bruce Clark United States
Radka Dziedzinská Czechia
Lvyan Tao China
Ju-Ju Qi China
Sylwia Parasion Poland
Mingda Hu relative to Deyvid Amgarten Brazil Deyvid Amgarten's profile →
Citations per field
00.5×2×2.7×
Deyvid Amgarten · 1×
Citations per year

Countries citing papers authored by Mingda Hu

Since Specialization
Citations

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

Fields of papers citing papers by Mingda Hu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 32 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202076
2 201434
3 201630
4 202325
5 201720
6 201718
7 202015
8 201713
9 202310
10 202110
11 20169
12 20228
13 20248
14 20246
15 20245
16 20234
17 20213
18 20213
19 20222
20 20222

About Mingda Hu

Mingda Hu is a scholar working on Infectious Diseases, Epidemiology, Agronomy and Crop Science, Molecular Medicine and Modeling and Simulation, having authored 32 papers that have together received 313 indexed citations. Recurring topics across this work include Influenza Virus Research Studies (8 papers), Viral gastroenteritis research and epidemiology (5 papers), Genomics and Phylogenetic Studies (5 papers), Animal Disease Management and Epidemiology (4 papers), SARS-CoV-2 and COVID-19 Research (4 papers), Bacteriophages and microbial interactions (4 papers), Antibiotic Resistance in Bacteria (3 papers) and RNA and protein synthesis mechanisms (3 papers). The work is most often cited by research in Endocrinology (33 citations), Agronomy and Crop Science (60 citations), Infectious Diseases (78 citations), Epidemiology (124 citations) and Molecular Medicine (13 citations). Mingda Hu has collaborated with scholars based in China, Czechia and Hong Kong. Frequent co-authors include Hongguang Ren, Junjie Yue, Long Liang, Jing Zhou, Jin Yuan, Beiping Li, Na Kong, Qi Zhang, Wei Zhou and Yuan Jin. Their work appears in journals such as Frontiers in Microbiology, BioMed Research International, Frontiers in Cellular and Infection Microbiology, BMC Genomics and Journal of Infection.

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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