Meng Ding
Impact in
- Cell Biology top 10%
- Zebrafish Biomedical Research Applications
- Hematology top 10%
- Hematopoietic Stem Cell Transplantation
Papers in
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- Sphingolipid Metabolism and Signaling 2
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- Adipose Tissue and Metabolism 5
- Co-authors
- Shifang Luan (3 shared papers)Wei Zhao (3 shared papers)Qi‐Qun Tang (10 shared papers)Shuwen Qian (10 shared papers)Tao Cheng (1 shared paper)Wenyan He (1 shared paper)Weiping Yuan (1 shared paper)Xiaohuan Mu (1 shared paper)
- Journals
- Journal of Biological Chemistry (3 papers)Plant Cell Tissue and Organ Culture (PCTOC) (2 papers)Advanced Functional Materials (1 paper)Diabetes (1 paper)Nature (1 paper)
- Partner nations
- ChinaUnited KingdomUnited States
In The Last Decade
Meng Ding
20 papers receiving 686 citations
Meng Ding's Hit Papers
Peers
Comparison fields: 5 of 110
- Cell Biology 144
- Hematology 82
- Molecular Biology 347
- Immunology 99
- Cancer Research 70
Countries citing papers authored by Meng Ding
This map shows the geographic impact of Meng Ding'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 Meng Ding with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Meng Ding more than expected).
Fields of papers citing papers by Meng Ding
This network shows the impact of papers produced by Meng Ding. 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 Meng Ding. The network helps show where Meng Ding may publish in the future.
Co-authors
The 25 scholars most cited alongside Meng Ding, 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 22 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 263 | |
| 2 | 2021 | 60 | |
| 3 | Artemisinins ameliorate polycystic ovarian syndrome by mediating LONP1-CYP11A1 interaction Hit paper breakdown → | 2024 | 53 |
| 4 | 2021 | 45 | |
| 5 | 2022 | 39 | |
| 6 | 2020 | 37 | |
| 7 | 2017 | 32 | |
| 8 | 2021 | 31 | |
| 9 | 2019 | 23 | |
| 10 | 2012 | 22 | |
| 11 | 2023 | 18 | |
| 12 | 2022 | 15 | |
| 13 | 2021 | 12 | |
| 14 | 2017 | 10 | |
| 15 | 2017 | 9 | |
| 16 | 2024 | 8 | |
| 17 | 2015 | 6 | |
| 18 | 2024 | 4 | |
| 19 | 2023 | 3 | |
| 20 | 2023 | 1 |
About Meng Ding
Meng Ding is a scholar working on Molecular Biology, Physiology, Epidemiology, Cell Biology and Biochemistry, having authored 22 papers that have together received 691 indexed citations. Recurring topics across this work include Adipose Tissue and Metabolism (5 papers), Nanoplatforms for cancer theranostics (3 papers), Lipid metabolism and biosynthesis (3 papers), Cancer, Hypoxia, and Metabolism (3 papers), Adipokines, Inflammation, and Metabolic Diseases (3 papers), Caveolin-1 and cellular processes (2 papers), Lipid metabolism and disorders (2 papers) and Sphingolipid Metabolism and Signaling (2 papers). The work is most often cited by research in Cell Biology (144 citations), Hematology (82 citations), Molecular Biology (347 citations), Immunology (99 citations) and Cancer Research (70 citations). Meng Ding has collaborated with scholars based in China, United Kingdom and United States. Frequent co-authors include Shifang Luan, Wei Zhao, Qi‐Qun Tang, Shuwen Qian, Tao Cheng, Wenyan He, Weiping Yuan, Xiaohuan Mu, Yanli Ni and Bing Liu. Their work appears in journals such as Journal of Biological Chemistry, Plant Cell Tissue and Organ Culture (PCTOC), Advanced Functional Materials, Diabetes and Nature.
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.