Ding Ding

985 citations
27 papers · 716 · h-index 15

Impact in

Papers in

Ding Ding

26 papers receiving 706 citations

Peers

Ding Ding
Comparison fields: 5 of 95
  • Endocrinology, Diabetes and Metabolism 105
  • Neurology 87
  • Cardiology and Cardiovascular Medicine 120
  • Nephrology 37
  • Pathology and Forensic Medicine 85
Replace An Song with:
An Song China
Yefeng Cai China
Aneta Aleksova Italy
Michelle J. Ormseth United States
David Karásek Czechia
Amira Adly Egypt
Zhihong Zhang China
Yequn Chen China
Andrea U. Steinbicker Germany
Elena Y. Senchenkova United States
Ding Ding relative to An Song China An Song's profile →
Citations per field
00.5×1.5×2.3×
An Song · 1×
Citations per year

Countries citing papers authored by Ding Ding

Since Specialization
Citations

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

Fields of papers citing papers by Ding Ding

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201891
2 202186
3 201373
4 201554
5 202249
6 201644
7 201344
8 201831
9 201431
10 201730
11 201527
12 201825
13 201317
14 201417
15 201515
16 201612
17 201611
18 202010
19 20169
20 20209

About Ding Ding

Ding Ding is a scholar working on Surgery, Cardiology and Cardiovascular Medicine, Epidemiology, Endocrinology, Diabetes and Metabolism and Pathology and Forensic Medicine, having authored 27 papers that have together received 716 indexed citations. Recurring topics across this work include Diabetes, Cardiovascular Risks, and Lipoproteins (6 papers), Lipoproteins and Cardiovascular Health (5 papers), Fatty Acid Research and Health (3 papers), Adipokines, Inflammation, and Metabolic Diseases (3 papers), Liver Disease Diagnosis and Treatment (3 papers), Vitamin D Research Studies (2 papers), Cardiovascular Disease and Adiposity (2 papers) and Cardiovascular Function and Risk Factors (2 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (105 citations), Neurology (87 citations), Cardiology and Cardiovascular Medicine (120 citations), Nephrology (37 citations) and Pathology and Forensic Medicine (85 citations). Ding Ding has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Wenhua Ling, Xinrui Li, Dongfang Su, Yuan Zhang, Gang Hu, Min Xia, Jian Qiu, Zhongxia Li, Yu‐Ming Chen and Dongliang Wang. Their work appears in journals such as PLoS ONE, Atherosclerosis, The Journal of Clinical Endocrinology & Metabolism, Oncotarget and Multiple Sclerosis and Related Disorders.

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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