Jun Dai

3.5k citations
155 papers · 2.7k · h-index 30

Impact in

    • Gastrointestinal Bleeding Diagnosis and Treatment
    • Cancer-related molecular mechanisms research
    • MicroRNA in disease regulation

Papers in

Jun Dai

144 papers receiving 2.6k citations

Peers

Jun Dai
Comparison fields: 5 of 172
  • Gastroenterology 329
  • Cancer Research 332
  • Surgery 500
  • Pathology and Forensic Medicine 175
  • Reproductive Medicine 81
Replace Hiroyuki Sugihara with:
Hiroyuki Sugihara Japan
Teng Zhang China
Luca Morelli Italy
Quan Wang China
Chen Xu China
Rong Li China
Li Yang China
Jun Chen China
Hao Tang China
Hideki Fujii Japan
Jun Dai relative to Hiroyuki Sugihara Japan Hiroyuki Sugihara's profile →
Citations per field
00.5×4.6×
Hiroyuki Sugihara · 1×
Citations per year

Countries citing papers authored by Jun Dai

Since Specialization
Citations

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

Fields of papers citing papers by Jun Dai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 155 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016129
2 202096
3 200984
4 202283
5 201774
6 200772
7 202068
8 201256
9 201256
10 201654
11 201251
12 201547
13 201846
14 201846
15 201945
16 201344
17 201343
18 201742
19 201940
20 201940

About Jun Dai

Jun Dai is a scholar working on Molecular Biology, Surgery, Cancer Research, Oncology and Pulmonary and Respiratory Medicine, having authored 155 papers that have together received 2.7k indexed citations. Recurring topics across this work include Adrenal and Paraganglionic Tumors (19 papers), Cancer-related molecular mechanisms research (9 papers), Spine and Intervertebral Disc Pathology (9 papers), Gastrointestinal Bleeding Diagnosis and Treatment (8 papers), Hormonal Regulation and Hypertension (7 papers), Cancer, Hypoxia, and Metabolism (6 papers), Circular RNAs in diseases (6 papers) and Osteoarthritis Treatment and Mechanisms (5 papers). The work is most often cited by research in Gastroenterology (329 citations), Cancer Research (332 citations), Surgery (500 citations), Pathology and Forensic Medicine (175 citations) and Reproductive Medicine (81 citations). Jun Dai has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Diganta Das, Michael Pecht, Han Chen, Zhi‐Zheng Ge, Fukang Sun, Zhi Zheng Ge, Qiurong Ruan, Hongchao He, Yun–Jie Gao and Michael Ohadi. Their work appears in journals such as BMC Musculoskeletal Disorders, Oncotarget, Gastrointestinal Endoscopy, Medicine and Frontiers in Oncology.

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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