Li Fu
Impact in
- Cancer Research top 2%
- Breast Cancer Treatment Studies
- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
- Oncology top 5%
- Cancer Cells and Metastasis
Papers in
-
- Epigenetics and DNA Methylation 10
- RNA modifications and cancer 9
-
- Breast Cancer Treatment Studies 20
- Cancer-related molecular mechanisms research 10
- Co-authors
- Feng Gu (37 shared papers)Xiaojing Guo (17 shared papers)Xinmin Zhang (7 shared papers)Yu Fan (13 shared papers)Ronggang Lang (16 shared papers)Fangfang Liu (13 shared papers)Yongjie Ma (12 shared papers)Bo Xu (5 shared papers)
- Journals
- Breast Cancer Research and Treatment (5 papers)PLoS ONE (5 papers)Cancer Science (3 papers)Oncotarget (3 papers)American Journal Of Pathology (3 papers)
- Partner nations
- ChinaUnited StatesJapan
In The Last Decade
Li Fu
115 papers receiving 2.8k citations
Peers
Comparison fields: 5 of 121
- Cancer Research 963
- Oncology 917
- Pathology and Forensic Medicine 442
- Molecular Biology 1.5k
- Dermatology 173
Countries citing papers authored by Li Fu
This map shows the geographic impact of Li Fu'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 Li Fu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Li Fu more than expected).
Fields of papers citing papers by Li Fu
This network shows the impact of papers produced by Li Fu. 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 Li Fu. The network helps show where Li Fu may publish in the future.
Co-authors
The 25 scholars most cited alongside Li Fu, 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 119 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 184 | |
| 2 | 2012 | 182 | |
| 3 | 2012 | 101 | |
| 4 | 2008 | 97 | |
| 5 | 2012 | 94 | |
| 6 | 2011 | 93 | |
| 7 | 2016 | 67 | |
| 8 | 2015 | 64 | |
| 9 | 2016 | 63 | |
| 10 | 2009 | 60 | |
| 11 | 2015 | 59 | |
| 12 | 2021 | 58 | |
| 13 | Elevated Aurora B expression contributes to chemoresistance and poor prognosis in breast cancer. | 2015 | 55 |
| 14 | 2015 | 48 | |
| 15 | 2017 | 47 | |
| 16 | 2012 | 46 | |
| 17 | 2015 | 46 | |
| 18 | 2009 | 43 | |
| 19 | 2016 | 42 | |
| 20 | 2013 | 41 |
About Li Fu
Li Fu is a scholar working on Molecular Biology, Cancer Research, Oncology, Pathology and Forensic Medicine and Cell Biology, having authored 119 papers that have together received 2.8k indexed citations. Recurring topics across this work include Breast Cancer Treatment Studies (20 papers), Breast Lesions and Carcinomas (19 papers), Cancer Cells and Metastasis (16 papers), HER2/EGFR in Cancer Research (12 papers), Epigenetics and DNA Methylation (10 papers), Cancer-related molecular mechanisms research (10 papers), RNA modifications and cancer (9 papers) and Cancer and Skin Lesions (9 papers). The work is most often cited by research in Cancer Research (963 citations), Oncology (917 citations), Pathology and Forensic Medicine (442 citations), Molecular Biology (1.5k citations) and Dermatology (173 citations). Li Fu has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Feng Gu, Xiaojing Guo, Xinmin Zhang, Yu Fan, Ronggang Lang, Fangfang Liu, Yongjie Ma, Bo Xu, Xiaolong Qian and Yi-Ling Yang. Their work appears in journals such as Breast Cancer Research and Treatment, PLoS ONE, Cancer Science, Oncotarget and American Journal Of Pathology.
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.