Jin Ding

2.6k citations
86 papers · 1.7k · h-index 22

Impact in

  • Immunology top 10%
    • T-cell and B-cell Immunology
    • Immune Cell Function and Interaction
    • Systemic Lupus Erythematosus Research

Papers in

Jin Ding

79 papers receiving 1.7k citations

Peers

Jin Ding
Comparison fields: 5 of 120
  • Immunology 394
  • Rheumatology 242
  • Genetics 164
  • Oncology 404
  • Radiology, Nuclear Medicine and Imaging 233
Replace Akira Suwa with:
Akira Suwa Japan
Stephen Wax United States
Koji Yoshida Japan
Birgit Niederreiter Austria
Minghua Wu United States
Yosuke Tanaka Japan
Makoto Hamasaki Japan
Hongbin Cao United States
Oliver Bechter Belgium
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Jin Ding relative to Akira Suwa Japan Akira Suwa's profile →
Citations per field
00.5×4.6×
Akira Suwa · 1×
Citations per year

Countries citing papers authored by Jin Ding

Since Specialization
Citations

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

Fields of papers citing papers by Jin Ding

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 86 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2012151
2 2007132
3 2022115
4 2021105
5 202194
6 200589
7 200674
8 201067
9 201465
10 200351
11 200647
12 201242
13 201235
14 202333
15 202329
16 202128
17 201827
18 202225
19 201825
20 202124

About Jin Ding

Jin Ding is a scholar working on Radiology, Nuclear Medicine and Imaging, Oncology, Rheumatology, Molecular Biology and Pulmonary and Respiratory Medicine, having authored 86 papers that have together received 1.7k indexed citations. Recurring topics across this work include Radiopharmaceutical Chemistry and Applications (8 papers), Peptidase Inhibition and Analysis (7 papers), Spondyloarthritis Studies and Treatments (7 papers), Rheumatoid Arthritis Research and Therapies (6 papers), Vasculitis and related conditions (5 papers), Monoclonal and Polyclonal Antibodies Research (5 papers), Systemic Lupus Erythematosus Research (5 papers) and COVID-19 Clinical Research Studies (5 papers). The work is most often cited by research in Immunology (394 citations), Rheumatology (242 citations), Genetics (164 citations), Oncology (404 citations) and Radiology, Nuclear Medicine and Imaging (233 citations). Jin Ding has collaborated with scholars based in China, Ethiopia and United States. Frequent co-authors include Zhaohui Zheng, Ping Zhu, Zhenbiao Wu, Hua Zhu, Zhi Yang, Zhi‐Nan Chen, Xueyi Li, Ping Zhu, Yichuan Wang and Jun Jia. Their work appears in journals such as Molecular Pharmaceutics, European Journal of Nuclear Medicine and Molecular Imaging, The Journal of Rheumatology, Medicine and Clinical Rheumatology.

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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