Charlene Mao
Impact in
- Cancer Research top 1%
- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
- Immunology top 5%
- Immune Cell Function and Interaction
- IL-33, ST2, and ILC Pathways
- Immune cells in cancer
Papers in
- Immunology 11
- Immune Cell Function and Interaction 9
- T-cell and B-cell Immunology 3
- IL-33, ST2, and ILC Pathways 2
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- Cancer-related gene regulation 2
- Co-authors
- Michael A. Caligiuri (13 shared papers)Carlo M. Croce (3 shared papers)Gerard J. Nuovo (2 shared papers)Federica Calore (1 shared paper)Francesca Lovat (1 shared paper)Paolo Fadda (1 shared paper)Patrick Nana‐Sinkam (1 shared paper)Hansjüerg Alder (1 shared paper)
- Journals
- Blood (9 papers)Proceedings of the National Academy of Sciences (2 papers)The Journal of Immunology (1 paper)Nature Genetics (1 paper)Cell Reports (1 paper)
- Partner nations
- United StatesGermanyEthiopia
In The Last Decade
Charlene Mao
17 papers receiving 2.2k citations
Charlene Mao's Hit Papers
Peers
Comparison fields: 5 of 93
- Cancer Research 1.1k
- Immunology 692
- Molecular Biology 1.5k
- Hematology 106
- Oncology 204
Countries citing papers authored by Charlene Mao
This map shows the geographic impact of Charlene Mao'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 Charlene Mao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Charlene Mao more than expected).
Fields of papers citing papers by Charlene Mao
This network shows the impact of papers produced by Charlene Mao. 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 Charlene Mao. The network helps show where Charlene Mao may publish in the future.
Co-authors
The 25 scholars most cited alongside Charlene Mao, 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 | MicroRNAs bind to Toll-like receptors to induce prometastatic inflammatory response Hit paper breakdown → | 2012 | 1346 |
| 2 | 2012 | 176 | |
| 3 | 2010 | 173 | |
| 4 | 2015 | 157 | |
| 5 | 2005 | 136 | |
| 6 | 2014 | 82 | |
| 7 | 2013 | 54 | |
| 8 | 2012 | 53 | |
| 9 | 2017 | 27 | |
| 10 | 2004 | 21 | |
| 11 | 2024 | 7 | |
| 12 | 2021 | 5 | |
| 13 | 2014 | 3 | |
| 14 | 2009 | 3 | |
| 15 | 2023 | 2 | |
| 16 | 2018 | 1 | |
| 17 | 2022 | 1 | |
| 18 | 2024 | 0 |
About Charlene Mao
Charlene Mao is a scholar working on Immunology, Molecular Biology, Oncology, Hematology and Genetics, having authored 18 papers that have together received 2.2k indexed citations. Recurring topics across this work include Immune Cell Function and Interaction (9 papers), T-cell and B-cell Immunology (3 papers), Chronic Lymphocytic Leukemia Research (3 papers), Adolescent and Pediatric Healthcare (2 papers), Autoimmune and Inflammatory Disorders Research (2 papers), Viral-associated cancers and disorders (2 papers), Cancer-related gene regulation (2 papers) and IL-33, ST2, and ILC Pathways (2 papers). The work is most often cited by research in Cancer Research (1.1k citations), Immunology (692 citations), Molecular Biology (1.5k citations), Hematology (106 citations) and Oncology (204 citations). Charlene Mao has collaborated with scholars based in United States, Germany and Ethiopia. Frequent co-authors include Michael A. Caligiuri, Carlo M. Croce, Gerard J. Nuovo, Federica Calore, Francesca Lovat, Paolo Fadda, Patrick Nana‐Sinkam, Hansjüerg Alder, Alessio Paone and Ramasamy Santhanam. Their work appears in journals such as Blood, Proceedings of the National Academy of Sciences, The Journal of Immunology, Nature Genetics and Cell 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.