Qi Jin

1.7k citations
29 papers · 921 · h-index 16

Impact in

Papers in

Qi Jin

29 papers receiving 908 citations

Peers

Qi Jin
Comparison fields: 5 of 80
  • Infectious Diseases 291
  • Cardiology and Cardiovascular Medicine 312
  • Hematology 120
  • Agronomy and Crop Science 107
  • Animal Science and Zoology 68
Replace Elena Cherkasova with:
Elena Cherkasova United States
Weimin Tsai United States
Koon-Chu Yaiw Sweden
Eric A. Lefèvre United Kingdom
Joel W. Graff United States
Gagan Bajwa United States
Gerald Eder Austria
María C. Jaimes United States
Christopher J. Kuckleburg United States
Setsuko Ishida Japan
Qi Jin relative to Elena Cherkasova United States Elena Cherkasova's profile →
Citations per field
00.5×3.6×
Elena Cherkasova · 1×
Citations per year

Countries citing papers authored by Qi Jin

Since Specialization
Citations

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

Fields of papers citing papers by Qi Jin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2005192
2 202281
3 200278
4 201477
5 200269
6 199565
7 200254
8 200250
9 201347
10 200035
11 201129
12 201626
13 202017
14 201915
15 200315
16 201015
17 201413
18 202410
19 202110
20 20146

About Qi Jin

Qi Jin is a scholar working on Molecular Biology, Cardiology and Cardiovascular Medicine, Epidemiology, Immunology and Infectious Diseases, having authored 29 papers that have together received 921 indexed citations. Recurring topics across this work include Viral Infections and Immunology Research (7 papers), RNA and protein synthesis mechanisms (5 papers), Xenotransplantation and immune response (4 papers), Bone Metabolism and Diseases (3 papers), Viral gastroenteritis research and epidemiology (2 papers), Herpesvirus Infections and Treatments (2 papers), Animal Disease Management and Epidemiology (2 papers) and Acute Myeloid Leukemia Research (2 papers). The work is most often cited by research in Infectious Diseases (291 citations), Cardiology and Cardiovascular Medicine (312 citations), Hematology (120 citations), Agronomy and Crop Science (107 citations) and Animal Science and Zoology (68 citations). Qi Jin has collaborated with scholars based in China, United States and Switzerland. Frequent co-authors include Megan Sykes, Yong‐Guang Yang, Yaqing He, Linlin Li, Jie Dong, Junping Zhu, Hong Yang, Xingye Xu, Yafang Zhu and Masahiro Abe. Their work appears in journals such as Blood Cancer Journal, Journal of Clinical Microbiology, PLoS ONE, Blood and The FASEB Journal.

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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