Xiaoling Wang
Impact in
- Cancer Research top 5%
- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
- Molecular Biology top 10%
- RNA Research and Splicing
- RNA modifications and cancer
- RNA Interference and Gene Delivery
- Circular RNAs in diseases
- CRISPR and Genetic Engineering
Papers in
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- MicroRNA in disease regulation 6
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- Circular RNAs in diseases 6
- RNA Research and Splicing 5
- CRISPR and Genetic Engineering 5
- Retinoids in leukemia and cellular processes 4
- Protein Degradation and Inhibitors 4
- Genomics and Chromatin Dynamics 4
- Co-authors
- Kankan Wang (7 shared papers)Vera Huang (2 shared papers)Robert F. Place (2 shared papers)Long-Cheng Li (2 shared papers)Tom F. Lue (1 shared paper)Guiting Lin (1 shared paper)Ji Wang (1 shared paper)Yi Qin (1 shared paper)
- Journals
- PLoS ONE (3 papers)Blood (2 papers)Cancer Letters (2 papers)Frontiers of Medicine (2 papers)Scientific Reports (2 papers)
- Partner nations
- ChinaUnited StatesAustralia
In The Last Decade
Xiaoling Wang
52 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 100
- Cancer Research 339
- Molecular Biology 755
- Hematology 76
- Aging 9
- Nephrology 33
Countries citing papers authored by Xiaoling Wang
This map shows the geographic impact of Xiaoling Wang'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 Xiaoling Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaoling Wang more than expected).
Fields of papers citing papers by Xiaoling Wang
This network shows the impact of papers produced by Xiaoling Wang. 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 Xiaoling Wang. The network helps show where Xiaoling Wang may publish in the future.
Co-authors
The 25 scholars most cited alongside Xiaoling Wang, 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 59 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2010 | 154 | |
| 2 | 2021 | 95 | |
| 3 | 2024 | 72 | |
| 4 | 2020 | 62 | |
| 5 | 2005 | 51 | |
| 6 | 2016 | 49 | |
| 7 | 2023 | 48 | |
| 8 | 2009 | 48 | |
| 9 | 2012 | 41 | |
| 10 | 2015 | 40 | |
| 11 | 2015 | 39 | |
| 12 | 2014 | 32 | |
| 13 | 2009 | 29 | |
| 14 | 2016 | 29 | |
| 15 | 2021 | 29 | |
| 16 | 2021 | 27 | |
| 17 | 2017 | 26 | |
| 18 | 2010 | 26 | |
| 19 | 2015 | 24 | |
| 20 | 2014 | 23 |
About Xiaoling Wang
Xiaoling Wang is a scholar working on Cancer Research, Molecular Biology, Hematology, Oncology and Immunology, having authored 59 papers that have together received 1.2k indexed citations. Recurring topics across this work include Acute Myeloid Leukemia Research (7 papers), Circular RNAs in diseases (6 papers), MicroRNA in disease regulation (6 papers), RNA Research and Splicing (5 papers), CRISPR and Genetic Engineering (5 papers), Retinoids in leukemia and cellular processes (4 papers), Protein Degradation and Inhibitors (4 papers) and Genomics and Chromatin Dynamics (4 papers). The work is most often cited by research in Cancer Research (339 citations), Molecular Biology (755 citations), Hematology (76 citations), Aging (9 citations) and Nephrology (33 citations). Xiaoling Wang has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Kankan Wang, Vera Huang, Robert F. Place, Long-Cheng Li, Tom F. Lue, Guiting Lin, Ji Wang, Yi Qin, Xia Li and Guoqiang Chen. Their work appears in journals such as PLoS ONE, Blood, Cancer Letters, Frontiers of Medicine and Scientific Reports.
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.