Shuling Li
Impact in
- Cancer Research top 10%
- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
Papers in
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- Circular RNAs in diseases 4
-
- Cancer-related molecular mechanisms research 6
- MicroRNA in disease regulation 4
- Breast Cancer Treatment Studies 2
- Co-authors
- Xuehu Xu (5 shared papers)Shangbiao Wu (4 shared papers)Li Gong (3 shared papers)Chun Ma (2 shared papers)Yuandong Xu (4 shared papers)Yong Li (2 shared papers)Bixi Sun (1 shared paper)Lei Zhang (1 shared paper)
- Journals
- Journal of Pharmacy and Pharmacology (2 papers)Oncology Reports (2 papers)Drug Delivery (1 paper)Regulatory Peptides (1 paper)Kidney Medicine (1 paper)
- Partner nations
- ChinaUnited StatesJapan
In The Last Decade
Shuling Li
32 papers receiving 510 citations
Peers
Comparison fields: 5 of 129
- Cancer Research 142
- Nephrology 23
- Molecular Biology 207
- Information Systems 61
- Biological Psychiatry 5
Countries citing papers authored by Shuling Li
This map shows the geographic impact of Shuling Li'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 Shuling Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shuling Li more than expected).
Fields of papers citing papers by Shuling Li
This network shows the impact of papers produced by Shuling Li. 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 Shuling Li. The network helps show where Shuling Li may publish in the future.
Co-authors
The 25 scholars most cited alongside Shuling Li, 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 36 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 75 | |
| 2 | 2020 | 53 | |
| 3 | 2015 | 48 | |
| 4 | 2004 | 46 | |
| 5 | 2019 | 43 | |
| 6 | 2011 | 38 | |
| 7 | The potential value of miR-1 and miR-374b as biomarkers for colorectal cancer. | 2015 | 38 |
| 8 | 2016 | 37 | |
| 9 | 2013 | 33 | |
| 10 | The competing risks of death vs ESRD in Medicare beneficiaries 65+ with chronic kidney disease, CHF, and anemia | 2002 | 20 |
| 11 | 2015 | 15 | |
| 12 | 2008 | 12 | |
| 13 | 2018 | 10 | |
| 14 | 2020 | 8 | |
| 15 | 2018 | 8 | |
| 16 | 2009 | 7 | |
| 17 | 2018 | 7 | |
| 18 | 2021 | 5 | |
| 19 | 2025 | 5 | |
| 20 | 2010 | 3 |
About Shuling Li
Shuling Li is a scholar working on Molecular Biology, Cancer Research, Artificial Intelligence, Pulmonary and Respiratory Medicine and Economics and Econometrics, having authored 36 papers that have together received 531 indexed citations. Recurring topics across this work include Cancer-related molecular mechanisms research (6 papers), Circular RNAs in diseases (4 papers), MicroRNA in disease regulation (4 papers), Cognitive Computing and Networks (3 papers), Dialysis and Renal Disease Management (3 papers), Healthcare Policy and Management (2 papers), Breast Cancer Treatment Studies (2 papers) and Robotics and Automated Systems (2 papers). The work is most often cited by research in Cancer Research (142 citations), Nephrology (23 citations), Molecular Biology (207 citations), Information Systems (61 citations) and Biological Psychiatry (5 citations). Shuling Li has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Xuehu Xu, Shangbiao Wu, Li Gong, Chun Ma, Yuandong Xu, Yong Li, Bixi Sun, Lei Zhang, Xiaobing Wu and Nanqi Huang. Their work appears in journals such as Journal of Pharmacy and Pharmacology, Oncology Reports, Drug Delivery, Regulatory Peptides and Kidney Medicine.
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.