Suxiang Tong

28.2k citations
85 papers · 3.8k indexed · 1 hit paper · h-index 32
Topics
SARS-CoV-2 and COVID-19 Research (20 papers)Animal Virus Infections Studies (19 papers)Viral Infections and Vectors (18 papers)

In The Last Decade

Suxiang Tong

84 papers receiving 3.7k citations

Hit Papers

Emergence of SARS-CoV-2 B.1.1.7 Lineage — United States, ...20212026202220242021100200300400

Peers

Suxiang Tong
Comparison fields: 5 of 130
  • Infectious Diseases 2.4k
  • Epidemiology 1.0k
  • Animal Science and Zoology 699
  • Molecular Biology 618
  • Public Health, Environmental and Occupational Health 427
Replace Edison Luíz Durigon with:
Edison Luíz Durigon Brazil
Hoi‐Wah Tsoi Hong Kong
W. Paul Duprex United States
Beatrice H. L. Wong Hong Kong
Shuo Su China
Adam S. Lauring United States
Jean‐Claude Manuguerra France
Suzan D. Pas Netherlands
Nischay Mishra United States
Suxiang Tong relative to Edison Luíz Durigon Brazil Edison Luíz Durigon's profile →
Citations per field
00.5×1.5×1.9×
Edison Luíz Durigon · 1×
Citations per year

Countries citing papers authored by Suxiang Tong

Since Specialization
Citations

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

Fields of papers citing papers by Suxiang Tong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Suxiang Tong

This figure shows the co-authorship network connecting the top 25 collaborators of Suxiang Tong. A scholar is included among the top collaborators of Suxiang Tong based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Suxiang Tong. Suxiang Tong is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 1
3 2
4 3
5 2
6 1
7 58
8 35
9 30
10 21
11 9
12 288
13 31
14 95
15 75
16 141
17 98
18 4
19 14
20 6

About Suxiang Tong

Suxiang Tong is a scholar working on Infectious Diseases, Virology and Animal Science and Zoology, having authored 85 papers that have together received 3.8k indexed citations. Recurring topics across this work include SARS-CoV-2 and COVID-19 Research (20 papers), Animal Virus Infections Studies (19 papers) and Viral Infections and Vectors (18 papers). The work is most often cited by research in Infectious Diseases (2.4k citations), Animal Science and Zoology (699 citations) and Modeling and Simulation (246 citations). Suxiang Tong has collaborated with scholars based in United States, China and Australia. Frequent co-authors include Larry J. Anderson, Ying Tao, Tyrrell Conway, Ivan V. Kuzmin, Yàn Li, Shur-Wern Wang Chern, Mark A. Pallansch, Krista Queen, Richard W. Compans and Yan Li. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nature Communications and PLoS ONE.

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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