Ding Shi

556 citations
39 papers · 356 · h-index 11

Impact in

    • MicroRNA in disease regulation
    • Cancer-related molecular mechanisms research
    • Gut microbiota and health
    • Circular RNAs in diseases

Papers in

    • Esophageal and GI Pathology 6
    • Glycosylation and Glycoproteins Research 3
    • Heat shock proteins research 2
    • Circular RNAs in diseases 2

Ding Shi

36 papers receiving 353 citations

Peers

Ding Shi
Comparison fields: 5 of 92
  • Cancer Research 39
  • Molecular Biology 131
  • Computer Vision and Pattern Recognition 38
  • Gastroenterology 9
  • Surgery 66
Replace Yisen Huang with:
Yisen Huang China
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Luis Cano France
Mingxin Zhang China
Xiaojing Kang China
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Ding Shi relative to Yisen Huang China Yisen Huang's profile →
Citations per field
00.5×4.7×
Yisen Huang · 1×
Citations per year

Countries citing papers authored by Ding Shi

Since Specialization
Citations

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

Fields of papers citing papers by Ding Shi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 39 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202359
2 202349
3 201734
4 201916
5 200416
6 201415
7 202212
8 202112
9 201312
10 201912
11 201310
12 201910
13 20179
14 20128
15 20237
16 20187
17 20047
18 20196
19 20166
20 20215

About Ding Shi

Ding Shi is a scholar working on Surgery, Molecular Biology, Pulmonary and Respiratory Medicine, Biomedical Engineering and Physiology, having authored 39 papers that have together received 356 indexed citations. Recurring topics across this work include Esophageal and GI Pathology (6 papers), Glycosylation and Glycoproteins Research (3 papers), Non-Invasive Vital Sign Monitoring (3 papers), Diet and metabolism studies (3 papers), Foreign Body Medical Cases (2 papers), Heat shock proteins research (2 papers), Liver Disease Diagnosis and Treatment (2 papers) and Circular RNAs in diseases (2 papers). The work is most often cited by research in Cancer Research (39 citations), Molecular Biology (131 citations), Computer Vision and Pattern Recognition (38 citations), Gastroenterology (9 citations) and Surgery (66 citations). Ding Shi has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Yongpan Liu, Yating Li, Shengjie Li, Wenrui Wu, Aoxiang Zhuge, Mengnan Li, Meizhong Xu, Lanjuan Li, Liya Yang and Xiaoyuan Bian. Their work appears in journals such as World Journal of Gastroenterology, International Journal of Oncology, IEEE Access, Leukemia Research and Journal of Laparoendoscopic & Advanced Surgical Techniques.

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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