Kun Wang

5.3k citations
120 papers · 3.4k indexed · 1 hit paper · h-index 29

Impact in

    • Cancer-related molecular mechanisms research
    • MicroRNA in disease regulation
    • RNA modifications and cancer
    • Extracellular vesicles in disease
    • RNA Research and Splicing
    • RNA and protein synthesis mechanisms
    • Circular RNAs in diseases
    • Cancer-related gene regulation

Papers in

Kun Wang

115 papers receiving 3.4k citations

Hit Papers

Transcriptome-wide mapping reveals reversible and dynamic N1-methyladenosine methylome 2016 · 525 citations
5252016202620192022100200300400500

Peers

Kun Wang
Comparison fields: 5 of 136
  • Cancer Research 1.0k
  • Molecular Biology 2.2k
  • Agronomy and Crop Science 263
  • Building and Construction 148
  • Biotechnology 89
Replace Jinfeng Wang with:
Jinfeng Wang China
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Kun Wang relative to Jinfeng Wang China Jinfeng Wang's profile →
Citations per field
00.5×8.2×
Jinfeng Wang · 1×
Citations per year

Countries citing papers authored by Kun Wang

Since Specialization
Citations

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

Fields of papers citing papers by Kun Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 120 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Transcriptome-wide mapping reveals reversible and dynamic N1-methyladenosine methylome
Hit paper breakdown →
2016525
2 2017372
3 2014219
4 2014156
5 2017145
6 2014105
7 201882
8 201781
9 202278
10 200868
11 201767
12 201859
13 201958
14 201855
15 202354
16 202254
17 202045
18 201845
19 202045
20 201139

About Kun Wang

Kun Wang is a scholar working on Agronomy and Crop Science, Cancer Research, Molecular Biology, Nutrition and Dietetics and Aquatic Science, having authored 120 papers that have together received 3.4k indexed citations. Recurring topics across this work include Extracellular vesicles in disease (21 papers), Ruminant Nutrition and Digestive Physiology (15 papers), MicroRNA in disease regulation (10 papers), Plant Reproductive Biology (8 papers), Plant Physiology and Cultivation Studies (8 papers), Cancer-related molecular mechanisms research (7 papers), Anaerobic Digestion and Biogas Production (6 papers) and Advanced Welding Techniques Analysis (5 papers). The work is most often cited by research in Cancer Research (1.0k citations), Molecular Biology (2.2k citations), Agronomy and Crop Science (263 citations), Building and Construction (148 citations) and Biotechnology (89 citations). Kun Wang has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Xiaoyu Li, Chengqi Yi, Xushen Xiong, Xiaoting Shu, Shiqing Ma, Lixia Wang, Benhai Xiong, Xuemei Nan, Linshu Jiang and Shu‐Bing Qian. Their work appears in journals such as Journal of Dairy Science, Frontiers in Microbiology, Animals, Foods and Nutrients.

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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