Ming Gu
Impact in
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- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
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- RNA modifications and cancer
- Circular RNAs in diseases
- Protein Tyrosine Phosphatases
- Cancer-related gene regulation
Papers in
- Oncology 3
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- Cancer Genomics and Diagnostics 1
- Co-authors
- Philip W. Majerus (1 shared paper)Xinyu Zheng (5 shared papers)Ilka Warshawsky (1 shared paper)Haiyang Jiang (2 shared papers)Xiaowei Li (1 shared paper)Dawei Ge (1 shared paper)Yu Xu (1 shared paper)Wenhui Zheng (3 shared papers)
- Journals
- Frontiers in Oncology (2 papers)Signal Transduction and Targeted Therapy (1 paper)Lipids in Health and Disease (1 paper)Cellular Physiology and Biochemistry (1 paper)Alzheimer s & Dementia (1 paper)
- Partner nations
- ChinaUnited StatesSingapore
In The Last Decade
Ming Gu
17 papers receiving 519 citations
Peers
Comparison fields: 5 of 72
- Cancer Research 155
- Molecular Biology 337
- Immunology 70
- Cardiology and Cardiovascular Medicine 72
- Aging 6
Countries citing papers authored by Ming Gu
This map shows the geographic impact of Ming Gu'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 Ming Gu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ming Gu more than expected).
Fields of papers citing papers by Ming Gu
This network shows the impact of papers produced by Ming Gu. 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 Ming Gu. The network helps show where Ming Gu may publish in the future.
Co-authors
The 25 scholars most cited alongside Ming Gu, 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 | 2017 | 189 | |
| 2 | 1992 | 82 | |
| 3 | 2019 | 76 | |
| 4 | 2024 | 44 | |
| 5 | 2012 | 23 | |
| 6 | 2022 | 20 | |
| 7 | 2022 | 16 | |
| 8 | 2017 | 15 | |
| 9 | 2019 | 11 | |
| 10 | 2023 | 10 | |
| 11 | 2024 | 9 | |
| 12 | 2023 | 9 | |
| 13 | 2021 | 8 | |
| 14 | 2020 | 6 | |
| 15 | 2016 | 2 | |
| 16 | 2017 | 2 | |
| 17 | 2021 | 1 | |
| 18 | 2025 | 1 | |
| 19 | 2025 | 0 | |
| 20 | 2025 | 0 |
About Ming Gu
Ming Gu is a scholar working on Oncology, Cancer Research, Rheumatology, Neurology and Cognitive Neuroscience, having authored 20 papers that have together received 524 indexed citations. Recurring topics across this work include Cancer Genomics and Diagnostics (1 paper), COVID-19 Clinical Research Studies (1 paper), Cannabis and Cannabinoid Research (1 paper), Parkinson's Disease Mechanisms and Treatments (1 paper), Glycogen Storage Diseases and Myoclonus (1 paper), Neuroscience and Neural Engineering (1 paper), Glycosylation and Glycoproteins Research (1 paper) and EEG and Brain-Computer Interfaces (1 paper). The work is most often cited by research in Cancer Research (155 citations), Molecular Biology (337 citations), Immunology (70 citations), Cardiology and Cardiovascular Medicine (72 citations) and Aging (6 citations). Ming Gu has collaborated with scholars based in China, United States and Singapore. Frequent co-authors include Philip W. Majerus, Xinyu Zheng, Ilka Warshawsky, Haiyang Jiang, Xiaowei Li, Dawei Ge, Yu Xu, Wenhui Zheng, Hongtao Chen and Yuhe Zhou. Their work appears in journals such as Frontiers in Oncology, Signal Transduction and Targeted Therapy, Lipids in Health and Disease, Cellular Physiology and Biochemistry and Alzheimer s & Dementia.
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.