Jin Xiong

1.7k citations
31 papers · 567 indexed · h-index 15
Topics
SARS-CoV-2 and COVID-19 Research (4 papers)SARS-CoV-2 detection and testing (4 papers)Biosensors and Analytical Detection (3 papers)
Partner nations
ChinaUnited StatesCanada

In The Last Decade

Jin Xiong

30 papers receiving 561 citations

Peers

Jin Xiong
Comparison fields: 5 of 100
  • Infectious Diseases 212
  • Molecular Biology 180
  • Biomedical Engineering 97
  • Epidemiology 63
  • Computational Theory and Mathematics 58
Replace Shuqi Xiao with:
Shuqi Xiao China
Jin Soo Shin South Korea
Ya Zhao China
Kanghong Hu China
Junwei Niu China
Muhammad Imran Arshad Pakistan
David Shum South Korea
Chonsaeng Kim South Korea
Calli M. Lear-Rooney United States
Zhongpeng Zhao China
Jin Xiong relative to Shuqi Xiao China Shuqi Xiao's profile →
Citations per field
00.5×2.8×
Shuqi Xiao · 1×
Citations per year

Countries citing papers authored by Jin Xiong

Since Specialization
Citations

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

Fields of papers citing papers by Jin Xiong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jin Xiong

This figure shows the co-authorship network connecting the top 25 collaborators of Jin Xiong. A scholar is included among the top collaborators of Jin Xiong 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 Jin Xiong. Jin Xiong 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 1
2 1
3 0
4 5
5 21
6 9
7 1
8 16
9 7
10 26
11 24
12 76
13 67
14 26
15 21
16 6
17 18
18
On Relation between Modern Distance Education and Gansu Development
1
19
MRI of Blood Volume With MS 325 in Experimental Choroidal Melanoma
2
20
Marine Four Component Seismic Prospecting
1

About Jin Xiong

Jin Xiong is a scholar working on Infectious Diseases, Molecular Medicine and Agronomy and Crop Science, having authored 31 papers that have together received 567 indexed citations. Recurring topics across this work include SARS-CoV-2 and COVID-19 Research (4 papers), SARS-CoV-2 detection and testing (4 papers) and Biosensors and Analytical Detection (3 papers). The work is most often cited by research in Infectious Diseases (212 citations), Pharmacology (46 citations) and Computational Theory and Mathematics (58 citations). Jin Xiong has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Hongping Wei, Junping Yu, Shuqi Xiao, Bo Zhang, Raphael Nyaruaba, Yanan Zhang, Zhiming Yuan, Zhen Wang, Han‐Qing Ye and Qiu‐Yan Zhang. Their work appears in journals such as The Science of The Total Environment, The Plant Journal and Journal of Clinical Microbiology.

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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