Ling Gan
Impact in
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- Meat and Animal Product Quality
- Animal Nutrition and Physiology
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- Proteins in Food Systems
Papers in
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- Circular RNAs in diseases 2
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- Meat and Animal Product Quality 5
- Animal Nutrition and Physiology 3
- Co-authors
- Simin Feng (2 shared papers)Ping Shao (2 shared papers)Peilong Sun (2 shared papers)Xisheng Hu (2 shared papers)Chung S. Yang (1 shared paper)Anna B. Liu (1 shared paper)Zhuqing Dai (1 shared paper)Wenyun Lu (1 shared paper)
- Journals
- Foods (3 papers)BMC Neuroscience (2 papers)Veterinary Research (2 papers)Frontiers in Microbiology (2 papers)Scientific Reports (2 papers)
- Partner nations
- ChinaUnited StatesGermany
In The Last Decade
Ling Gan
25 papers receiving 317 citations
Peers
Comparison fields: 5 of 96
- Animal Science and Zoology 37
- Food Science 48
- Molecular Medicine 12
- Small Animals 17
- Biochemistry 13
Countries citing papers authored by Ling Gan
This map shows the geographic impact of Ling 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 Ling Gan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ling Gan more than expected).
Fields of papers citing papers by Ling Gan
This network shows the impact of papers produced by Ling 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 Ling Gan. The network helps show where Ling Gan may publish in the future.
Co-authors
The 25 scholars most cited alongside Ling Gan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 33 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 98 | |
| 2 | 2020 | 42 | |
| 3 | 2020 | 30 | |
| 4 | 2016 | 25 | |
| 5 | 2015 | 15 | |
| 6 | 2016 | 15 | |
| 7 | 2015 | 13 | |
| 8 | 2011 | 13 | |
| 9 | 2016 | 12 | |
| 10 | 2009 | 9 | |
| 11 | 2020 | 8 | |
| 12 | 2023 | 8 | |
| 13 | 2024 | 7 | |
| 14 | 2024 | 5 | |
| 15 | 2017 | 4 | |
| 16 | 2016 | 3 | |
| 17 | 2019 | 3 | |
| 18 | 2018 | 2 | |
| 19 | 2021 | 2 | |
| 20 | 2025 | 2 |
About Ling Gan
Ling Gan is a scholar working on Molecular Biology, Animal Science and Zoology, Epidemiology, Food Science and Cancer Research, having authored 33 papers that have together received 322 indexed citations. Recurring topics across this work include Meat and Animal Product Quality (5 papers), Herpesvirus Infections and Treatments (4 papers), Cancer-related molecular mechanisms research (3 papers), Animal Nutrition and Physiology (3 papers), Mosquito-borne diseases and control (3 papers), Cardiovascular Health and Disease Prevention (2 papers), Animal Behavior and Welfare Studies (2 papers) and Circular RNAs in diseases (2 papers). The work is most often cited by research in Animal Science and Zoology (37 citations), Food Science (48 citations), Molecular Medicine (12 citations), Small Animals (17 citations) and Biochemistry (13 citations). Ling Gan has collaborated with scholars based in China, United States and Germany. Frequent co-authors include Simin Feng, Ping Shao, Peilong Sun, Xisheng Hu, Chung S. Yang, Anna B. Liu, Zhuqing Dai, Wenyun Lu, Zisheng Luo and Dan Wang. Their work appears in journals such as Foods, BMC Neuroscience, Veterinary Research, Frontiers in Microbiology and Scientific Reports.
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.