Xulong Wu

474 citations
36 papers · 356 · h-index 12

Impact in

Papers in

Xulong Wu

35 papers receiving 348 citations

Peers

Xulong Wu
Comparison fields: 5 of 85
  • Agronomy and Crop Science 63
  • Animal Science and Zoology 61
  • Infectious Diseases 61
  • Biological Psychiatry 8
  • Microbiology 18
Replace Qiwen Wu with:
Qiwen Wu China
Seog-Jin Kang South Korea
Junsheng Dong China
Manijeh Mohammadi‐Dehcheshmeh Australia
Yanhan Liu China
Jiansong You China
Alzahraa M. Abdelatty Egypt
Zi Xie China
María Muñoz Spain
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Citations per field
00.5×2.7×
Qiwen Wu · 1×
Citations per year

Countries citing papers authored by Xulong Wu

Since Specialization
Citations

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

Fields of papers citing papers by Xulong Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 36 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202239
2 201728
3
Development and application of a droplet digital polymerase chain reaction (ddPCR) for detection and investigation of African swine fever virus.
201821
4 202119
5 202219
6 202019
7 202118
8 202117
9 201617
10 201812
11 202112
12 201511
13 201910
14 20189
15 20179
16 20209
17 20209
18 20227
19 20227
20 20217

About Xulong Wu

Xulong Wu is a scholar working on Molecular Biology, Infectious Diseases, Animal Science and Zoology, Agronomy and Crop Science and Cancer Research, having authored 36 papers that have together received 356 indexed citations. Recurring topics across this work include Animal Virus Infections Studies (8 papers), Viral gastroenteritis research and epidemiology (8 papers), Animal Disease Management and Epidemiology (5 papers), Viral Infections and Immunology Research (4 papers), RNA Research and Splicing (3 papers), MicroRNA in disease regulation (3 papers), Streptococcal Infections and Treatments (2 papers) and Cancer-related molecular mechanisms research (2 papers). The work is most often cited by research in Agronomy and Crop Science (63 citations), Animal Science and Zoology (61 citations), Infectious Diseases (61 citations), Biological Psychiatry (8 citations) and Microbiology (18 citations). Xulong Wu has collaborated with scholars based in China, Hong Kong and Switzerland. Frequent co-authors include Zexiao Yang, Xueping Yao, Li Su, Lulu Zhu, Jianxiong Long, Jialei Yang, Yin Wang, Zizhong Tang, Lin Hua and Miao Yang. Their work appears in journals such as Journal of Molecular Neuroscience, PeerJ, Genes Brain & Behavior, BioMed Research International and Neurological Sciences.

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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