Wu Gan

462 citations
37 papers · 336 · h-index 10

Impact in

Papers in

Wu Gan

33 papers receiving 332 citations

Peers

Wu Gan
Comparison fields: 5 of 91
  • Health, Toxicology and Mutagenesis 56
  • Animal Science and Zoology 35
  • Aquatic Science 24
  • Physiology 11
  • Immunology 36
Replace Mohammed S. Al‐Ayed with:
Mohammed S. Al‐Ayed Saudi Arabia
Chenghui Wang China
Samuel Herianto Taiwan
Sascha Nicklisch United States
Ruiqi Fan China
Nana Zhang China
Xiaoqing Tan China
Zeeshan Ali China
Jang-Su Park South Korea
Jayeeta Banerjee India
Wu Gan relative to Mohammed S. Al‐Ayed Saudi Arabia Mohammed S. Al‐Ayed's profile →
Citations per field
00.5×2.9×
Mohammed S. Al‐Ayed · 1×
Citations per year

Countries citing papers authored by Wu Gan

Since Specialization
Citations

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

Fields of papers citing papers by Wu Gan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202241
2 202440
3 202338
4 202236
5 202322
6 202022
7 202121
8 202321
9 20229
10 20229
11 20208
12 20208
13
Non-isolated High Step-up DC-DC Converters Adopting Switched-capacitor Cell
20157
14 20246
15 20236
16 20205
17 20214
18 20204
19 20224
20 20243

About Wu Gan

Wu Gan is a scholar working on Molecular Biology, Cancer Research, Health, Toxicology and Mutagenesis, Genetics and Electrical and Electronic Engineering, having authored 37 papers that have together received 336 indexed citations. Recurring topics across this work include Cancer-related molecular mechanisms research (6 papers), Air Quality and Health Impacts (5 papers), MicroRNA in disease regulation (5 papers), Climate Change and Health Impacts (4 papers), Circular RNAs in diseases (3 papers), Meat and Animal Product Quality (3 papers), Piezoelectric Actuators and Control (3 papers) and Aquaculture disease management and microbiota (3 papers). The work is most often cited by research in Health, Toxicology and Mutagenesis (56 citations), Animal Science and Zoology (35 citations), Aquatic Science (24 citations), Physiology (11 citations) and Immunology (36 citations). Wu Gan has collaborated with scholars based in China, United States and Taiwan. Frequent co-authors include Zhaoyang Ding, Jing Xie, Hualiang Lin, Chongjian Wang, Jing Xie, Xiaojie Wang, Xiaoyu Du, Jun Mei, Huijie Yu and Hongtao Zou. Their work appears in journals such as Food Chemistry, Frontiers in Genetics, Scientific Reports, International Journal of Food Microbiology and American Journal of Clinical Nutrition.

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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