Xingchen Wu

1.5k citations
54 papers · 1.2k · h-index 20

Impact in

Papers in

Xingchen Wu

52 papers receiving 1.2k citations

Peers

Xingchen Wu
Comparison fields: 5 of 95
  • Pathology and Forensic Medicine 261
  • Animal Science and Zoology 138
  • Renewable Energy, Sustainability and the Environment 191
  • Radiology, Nuclear Medicine and Imaging 190
  • Catalysis 64
Replace Susan H. Hsu with:
Susan H. Hsu United States
Kenji Sugawara Japan
Linhui Wang China
Shanyu Chen China
Guanghua Wang China
Hiroshi Harada Japan
Wolfgang Pfützner Germany
Julia Steitz Germany
Yoshinori Makino Japan
Meiling Shen China
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Citations per field
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Citations per year

Countries citing papers authored by Xingchen Wu

Since Specialization
Citations

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

Fields of papers citing papers by Xingchen Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 54 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2018226
2 201185
3 201163
4 202160
5 201858
6 201257
7 201655
8 200442
9 201237
10 201936
11 201934
12 201133
13 201832
14 201827
15 201125
16 201424
17 201123
18 200722
19 201321
20 201621

About Xingchen Wu

Xingchen Wu is a scholar working on Pathology and Forensic Medicine, Animal Science and Zoology, Molecular Biology, Radiology, Nuclear Medicine and Imaging and Genetics, having authored 54 papers that have together received 1.2k indexed citations. Recurring topics across this work include Animal Virus Infections Studies (11 papers), Lymphoma Diagnosis and Treatment (9 papers), Multiple Sclerosis Research Studies (8 papers), Virus-based gene therapy research (8 papers), MRI in cancer diagnosis (6 papers), RNA Interference and Gene Delivery (4 papers), Viral gastroenteritis research and epidemiology (4 papers) and Viral Infections and Immunology Research (4 papers). The work is most often cited by research in Pathology and Forensic Medicine (261 citations), Animal Science and Zoology (138 citations), Renewable Energy, Sustainability and the Environment (191 citations), Radiology, Nuclear Medicine and Imaging (190 citations) and Catalysis (64 citations). Xingchen Wu has collaborated with scholars based in China, Finland and United States. Frequent co-authors include Pirkko‐Liisa Kellokumpu‐Lehtinen, Chenxin Cai, Prasun Dastidar, Hannu Pertovaara, Ping Wu, Hannu Eskola, Zhewei Cai, Yuan Gao, Qian Du and Yong Huang. Their work appears in journals such as Veterinary Sciences, Frontiers in Immunology, Viruses, The Journal of Immunology and Journal of Integrative Agriculture.

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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