Dan Su

1.6k citations
72 papers · 1.1k · h-index 20

Impact in

    • MicroRNA in disease regulation
    • Cancer-related molecular mechanisms research
  • Health top 10%
    • Health disparities and outcomes

Papers in

    • Circular RNAs in diseases 4
    • RNA modifications and cancer 4
    • MicroRNA in disease regulation 10
    • Cancer-related molecular mechanisms research 7

Dan Su

66 papers receiving 1.1k citations

Peers

Dan Su
Comparison fields: 5 of 127
  • Cancer Research 214
  • Health 86
  • Neuropsychology and Physiological Psychology 14
  • Molecular Biology 465
  • Endocrinology, Diabetes and Metabolism 103
Replace Shengnan Chen with:
Shengnan Chen China
Minoru Isomura Japan
Ben Zhang China
Lei Su China
Silviu Cristian Voinea Romania
Weiyi Lai China
Zhaoyang Li United States
Fei Wu China
Linfeng Zheng China
You Li China
Dan Su relative to Shengnan Chen China Shengnan Chen's profile →
Citations per field
00.5×2.7×
Shengnan Chen · 1×
Citations per year

Countries citing papers authored by Dan Su

Since Specialization
Citations

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

Fields of papers citing papers by Dan Su

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 72 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2012122
2 201374
3 200764
4 201750
5 201749
6 201749
7 201543
8 202040
9 201038
10 201632
11 201331
12 201628
13 201327
14 202126
15 201525
16 202125
17 202122
18 201421
19 201721
20 201620

About Dan Su

Dan Su is a scholar working on Molecular Biology, Cancer Research, Oncology, Surgery and Cardiology and Cardiovascular Medicine, having authored 72 papers that have together received 1.1k indexed citations. Recurring topics across this work include MicroRNA in disease regulation (10 papers), Blood Pressure and Hypertension Studies (7 papers), Cancer-related molecular mechanisms research (7 papers), Cardiovascular Health and Disease Prevention (5 papers), Circular RNAs in diseases (4 papers), RNA modifications and cancer (4 papers), Heart Rate Variability and Autonomic Control (4 papers) and Nanoplatforms for cancer theranostics (4 papers). The work is most often cited by research in Cancer Research (214 citations), Health (86 citations), Neuropsychology and Physiological Psychology (14 citations), Molecular Biology (465 citations) and Endocrinology, Diabetes and Metabolism (103 citations). Dan Su has collaborated with scholars based in China, United States and Thailand. Frequent co-authors include Xianning Wu, Huiping Li, Jingping Zhang, Leshan Zhou, Yingxin Zhang, Bin Yan, Luan Wen, Yun‐Bo Shi, Pengcheng Chen and Jianguo Feng. Their work appears in journals such as Molecular Therapy — Nucleic Acids, Scientific Reports, Journal of Biological Chemistry, Clinical Cardiology and Biochemical Society Transactions.

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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