Mingda Hu

418 citations
27 papers · 261 · h-index 9

Impact in

Papers in

    • Influenza Virus Research Studies 7
    • Viral gastroenteritis research and epidemiology 3
    • SARS-CoV-2 and COVID-19 Research 3

Mingda Hu

22 papers receiving 256 citations

Peers

Mingda Hu
Comparison fields: 5 of 64
  • Endocrinology 33
  • Agronomy and Crop Science 42
  • Infectious Diseases 57
  • Epidemiology 92
  • Molecular Medicine 13
Replace Beiping Li with:
Beiping Li China
Yunrong Gao United States
Chunmao Zhang China
Kimberly R. Davis United States
Christophe Audebert France
Bede Constantinides United Kingdom
Keylie M. Gibson United States
Bruce Clark United States
Ana G. Cobián-Güemes United States
Deyvid Amgarten Brazil
Mingda Hu relative to Beiping Li China Beiping Li's profile →
Citations per field
00.5×
Beiping Li · 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 27 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202075
2 201433
3 201627
4 202324
5 201716
6 202015
7 201713
8 20238
9 20248
10 20167
11 20217
12 20246
13 20234
14 20244
15 20213
16 20253
17 20222
18 20222
19 20251
20 20211

About Mingda Hu

Mingda Hu is a scholar working on Epidemiology, Infectious Diseases, Molecular Biology, Ecology and Agronomy and Crop Science, having authored 27 papers that have together received 261 indexed citations. Recurring topics across this work include Influenza Virus Research Studies (7 papers), Genomics and Phylogenetic Studies (4 papers), Bacteriophages and microbial interactions (4 papers), Viral gastroenteritis research and epidemiology (3 papers), Animal Disease Management and Epidemiology (3 papers), SARS-CoV-2 and COVID-19 Research (3 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 (42 citations), Infectious Diseases (57 citations), Epidemiology (92 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, Qi Zhang, Na Kong, Wei Zhou and Yuan Jin. Their work appears in journals such as Frontiers in Microbiology, Frontiers in Cellular and Infection Microbiology, BioMed Research International, BMC Genomics and Signal Transduction and Targeted Therapy.

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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