Mingda Yan
Impact in
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- Cancer, Hypoxia, and Metabolism
- Biochemistry top 10%
Papers in
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- Peroxisome Proliferator-Activated Receptors 5
- Sphingolipid Metabolism and Signaling 3
- Protein Kinase Regulation and GTPase Signaling 2
- RNA Research and Splicing 2
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- Caveolin-1 and cellular processes 3
- Co-authors
- Suresh Subramani (5 shared papers)Naganand Rayapuram (2 shared papers)Zhongcheng Zheng (6 shared papers)Xinyuan Liu (5 shared papers)Lanying Sun (5 shared papers)Weijing Xu (4 shared papers)Weiguo Zou (2 shared papers)Hairong Huo (1 shared paper)
- Journals
- Biochemical and Biophysical Research Communications (2 papers)Genes & Cancer (2 papers)Cancer Letters (1 paper)Molecular Biology of the Cell (1 paper)Journal of Cellular Biochemistry (1 paper)
- Partner nations
- United StatesChinaSouth Korea
In The Last Decade
Mingda Yan
20 papers receiving 815 citations
Peers
Comparison fields: 5 of 91
- Cancer Research 132
- Biochemistry 60
- Molecular Biology 562
- Cell Biology 98
- Toxicology 14
Countries citing papers authored by Mingda Yan
This map shows the geographic impact of Mingda Yan'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 Mingda Yan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mingda Yan more than expected).
Fields of papers citing papers by Mingda Yan
This network shows the impact of papers produced by Mingda Yan. 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 Mingda Yan. The network helps show where Mingda Yan may publish in the future.
Co-authors
The 25 scholars most cited alongside Mingda Yan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2001 | 164 | |
| 2 | 2006 | 137 | |
| 3 | 2005 | 107 | |
| 4 | 2014 | 86 | |
| 5 | 2018 | 71 | |
| 6 | 2007 | 68 | |
| 7 | 2017 | 48 | |
| 8 | 1998 | 32 | |
| 9 | 2003 | 15 | |
| 10 | 2020 | 14 | |
| 11 | 2015 | 14 | |
| 12 | 2016 | 13 | |
| 13 | 2001 | 12 | |
| 14 | 2021 | 11 | |
| 15 | 2024 | 9 | |
| 16 | 2000 | 7 | |
| 17 | 2021 | 6 | |
| 18 | 2015 | 5 | |
| 19 | 2003 | 3 | |
| 20 | 2007 | 3 |
About Mingda Yan
Mingda Yan is a scholar working on Molecular Biology, Cell Biology, Immunology, Cancer Research and Oncology, having authored 20 papers that have together received 825 indexed citations. Recurring topics across this work include Peroxisome Proliferator-Activated Receptors (5 papers), interferon and immune responses (3 papers), Sphingolipid Metabolism and Signaling (3 papers), Caveolin-1 and cellular processes (3 papers), Cytokine Signaling Pathways and Interactions (3 papers), Protein Kinase Regulation and GTPase Signaling (2 papers), RNA Research and Splicing (2 papers) and Bioactive Compounds and Antitumor Agents (2 papers). The work is most often cited by research in Cancer Research (132 citations), Biochemistry (60 citations), Molecular Biology (562 citations), Cell Biology (98 citations) and Toxicology (14 citations). Mingda Yan has collaborated with scholars based in United States, China and South Korea. Frequent co-authors include Suresh Subramani, Naganand Rayapuram, Zhongcheng Zheng, Xinyuan Liu, Lanying Sun, Weijing Xu, Weiguo Zou, Hairong Huo, Danny N. Dhanasekaran and Muralidharan Jayaraman. Their work appears in journals such as Biochemical and Biophysical Research Communications, Genes & Cancer, Cancer Letters, Molecular Biology of the Cell and Journal of Cellular Biochemistry.
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.