Xiaohong Wu

8.9k citations
164 papers · 4.0k · 1 hit paper · h-index 34

Impact in

Papers in

Xiaohong Wu

158 papers receiving 3.9k citations

Xiaohong Wu's Hit Papers

Advances in COVID-19 mRNA vaccine development 2022 · 400 citations
4000+1+2Years since publication100200300400

Peers

Xiaohong Wu
Comparison fields: 5 of 160
  • Immunology 596
  • Endocrinology, Diabetes and Metabolism 397
  • Geriatrics and Gerontology 66
  • Infectious Diseases 325
  • Virology 83
Replace Kazunori Shimada with:
Kazunori Shimada Japan
Yong Jiang China
Dandan Li China
Hideki Nomura Japan
Luc Camoin France
Yutaka Eguchi Japan
Bernd Thiede Norway
Marcus F. Oliveira Brazil
Anil B. Mukherjee United States
Haiying Sun China
Xiaohong Wu relative to Kazunori Shimada Japan Kazunori Shimada's profile →
Citations per field
00.5×4.9×
Kazunori Shimada · 1×
Citations per year

Countries citing papers authored by Xiaohong Wu

Since Specialization
Citations

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

Fields of papers citing papers by Xiaohong Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 164 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Advances in COVID-19 mRNA vaccine development
Hit paper breakdown →
2022400
2 2009153
3 2013152
4 2010150
5 2008127
6 200494
7 201392
8 201892
9 200288
10 200787
11 201378
12 201171
13 202165
14 201563
15 201958
16 201758
17 201454
18 201353
19 201151
20 199948

About Xiaohong Wu

Xiaohong Wu is a scholar working on Molecular Biology, Endocrinology, Diabetes and Metabolism, Oncology, Immunology and Surgery, having authored 164 papers that have together received 4.0k indexed citations. Recurring topics across this work include Pancreatic function and diabetes (9 papers), Thyroid Cancer Diagnosis and Treatment (9 papers), Yersinia bacterium, plague, ectoparasites research (7 papers), Rabies epidemiology and control (7 papers), Neuroinflammation and Neurodegeneration Mechanisms (6 papers), Neurogenesis and neuroplasticity mechanisms (5 papers), HER2/EGFR in Cancer Research (5 papers) and Inflammatory Biomarkers in Disease Prognosis (5 papers). The work is most often cited by research in Immunology (596 citations), Endocrinology, Diabetes and Metabolism (397 citations), Geriatrics and Gerontology (66 citations), Infectious Diseases (325 citations) and Virology (83 citations). Xiaohong Wu has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Yuhua Li, M. Firoze Khan, Iwao Ojima, Danhua Zhao, Jingjing Liu, Enyue Fang, Xiaohui Liu, Zelun Zhang, Miao Li and Lifang Song. Their work appears in journals such as Scientific Reports, Journal of Molecular Histology, PLoS ONE, Human Vaccines & Immunotherapeutics and Neurochemical Research.

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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