Yan Gu
Impact in
- Cancer Research top 1%
- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
- Immunology top 5%
- Immune Cell Function and Interaction
- Immune cells in cancer
- Immunotherapy and Immune Responses
Papers in
-
- Circular RNAs in diseases 5
- Hematology 18
- Multiple Myeloma Research and Treatments 7
- Chronic Myeloid Leukemia Treatments 6
- Acute Myeloid Leukemia Research 6
- Co-authors
- Xuetao Cao (11 shared papers)Yanfang Liu (3 shared papers)Jin Hou (4 shared papers)Yizhi Yu (2 shared papers)Xiaoping Su (3 shared papers)Cheng Qian (3 shared papers)Yun Lin (1 shared paper)Xiang Liu (1 shared paper)
- Journals
- Blood (6 papers)Oncotarget (6 papers)Scientific Reports (5 papers)Hepatology (2 papers)Cellular Physiology and Biochemistry (2 papers)
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Yan Gu
86 papers receiving 3.1k citations
Yan Gu's Hit Papers
Peers
Comparison fields: 5 of 119
- Cancer Research 1.1k
- Immunology 558
- Molecular Biology 1.8k
- Hematology 215
- Oncology 394
Countries citing papers authored by Yan Gu
This map shows the geographic impact of Yan 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 Yan Gu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yan Gu more than expected).
Fields of papers citing papers by Yan Gu
This network shows the impact of papers produced by Yan 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 Yan Gu. The network helps show where Yan Gu may publish in the future.
Co-authors
The 25 scholars most cited alongside Yan 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
Showing the 20 most-cited of 91 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Circular RNA circMTO1 acts as the sponge of microRNA‐9 to suppress hepatocellular carcinoma progression Hit paper breakdown → | 2017 | 956 |
| 2 | 2013 | 193 | |
| 3 | 2015 | 188 | |
| 4 | 2019 | 156 | |
| 5 | 2012 | 119 | |
| 6 | 2017 | 89 | |
| 7 | 2016 | 77 | |
| 8 | 2005 | 77 | |
| 9 | 2018 | 71 | |
| 10 | 2017 | 62 | |
| 11 | 2017 | 60 | |
| 12 | 2013 | 56 | |
| 13 | 2017 | 50 | |
| 14 | 2009 | 49 | |
| 15 | 2005 | 43 | |
| 16 | 2019 | 40 | |
| 17 | 2018 | 39 | |
| 18 | 2021 | 38 | |
| 19 | 2015 | 37 | |
| 20 | 2004 | 36 |
About Yan Gu
Yan Gu is a scholar working on Molecular Biology, Hematology, Oncology, Public Health, Environmental and Occupational Health and Immunology, having authored 91 papers that have together received 3.1k indexed citations. Recurring topics across this work include Acute Lymphoblastic Leukemia research (12 papers), Multiple Myeloma Research and Treatments (7 papers), Childhood Cancer Survivors' Quality of Life (6 papers), Chronic Myeloid Leukemia Treatments (6 papers), Acute Myeloid Leukemia Research (6 papers), Cancer-related molecular mechanisms research (5 papers), MicroRNA in disease regulation (5 papers) and Circular RNAs in diseases (5 papers). The work is most often cited by research in Cancer Research (1.1k citations), Immunology (558 citations), Molecular Biology (1.8k citations), Hematology (215 citations) and Oncology (394 citations). Yan Gu has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Xuetao Cao, Yanfang Liu, Jin Hou, Yizhi Yu, Xiaoping Su, Cheng Qian, Yun Lin, Xiang Liu, Jiangxue Li and Mingyan Huang. Their work appears in journals such as Blood, Oncotarget, Scientific Reports, Hepatology and Cellular Physiology and 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.