Kun Shang

1.9k citations
79 papers · 1.5k · h-index 22

Impact in

    • Venous Thromboembolism Diagnosis and Management
    • MicroRNA in disease regulation
    • Cancer-related molecular mechanisms research

Papers in

Kun Shang

77 papers receiving 1.5k citations

Peers

Kun Shang
Comparison fields: 5 of 114
  • Internal Medicine 84
  • Cancer Research 152
  • Animal Science and Zoology 89
  • Immunology 160
  • Food Science 129
Replace Silvia Montoro‐García with:
Silvia Montoro‐García Spain
Yanhua Wang China
Qiang Zhou China
Haifeng Huang China
Francesca Felice Italy
Rita Müller Germany
Tong Li China
Mao Luo China
Xiaolu Li China
Kun Shang relative to Silvia Montoro‐García Spain Silvia Montoro‐García's profile →
Citations per field
00.5×2×3×4.2×
Silvia Montoro‐García · 1×
Citations per year

Countries citing papers authored by Kun Shang

Since Specialization
Citations

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

Fields of papers citing papers by Kun Shang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 79 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2012121
2 201597
3 201990
4 202171
5 201862
6 202260
7 201855
8 201848
9 202044
10 202036
11 201435
12 202034
13 201834
14 202334
15 201431
16 202530
17 201925
18 202525
19 202124
20 202024

About Kun Shang

Kun Shang is a scholar working on Molecular Biology, Internal Medicine, Cancer Research, Immunology and Pulmonary and Respiratory Medicine, having authored 79 papers that have together received 1.5k indexed citations. Recurring topics across this work include Nanoplatforms for cancer theranostics (5 papers), Epilepsy research and treatment (4 papers), Venous Thromboembolism Diagnosis and Management (4 papers), Immune cells in cancer (4 papers), RNA modifications and cancer (3 papers), Molecular Sensors and Ion Detection (3 papers), Phytochemistry and Biological Activities (3 papers) and Coronary Artery Anomalies (3 papers). The work is most often cited by research in Internal Medicine (84 citations), Cancer Research (152 citations), Animal Science and Zoology (89 citations), Immunology (160 citations) and Food Science (129 citations). Kun Shang has collaborated with scholars based in China, United States and France. Frequent co-authors include Bangwei Cao, Jinyu Chen, Kunsheng Zhang, Chao Ke, Yan Zhuang, Pengfei Wang, Yuxin Pei, Zhichao Pei, Bin-Fei Zhang and Dian Zhang. Their work appears in journals such as Frontiers in Pharmacology, Epilepsy Research, BioMed Research International, Chinese Chemical Letters and International Journal of Nanomedicine.

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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