Mei-Ling Ai
Impact in
- Cancer Research top 10%
- Cancer-related molecular mechanisms research
- MicroRNA in disease regulation
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- RNA modifications and cancer
- Circular RNAs in diseases
- RNA Research and Splicing
Papers in ⓘ
-
- Cancer-related molecular mechanisms research 7
- MicroRNA in disease regulation 2
- Oncology 5
- Peptidase Inhibition and Analysis 2
- Co-authors
- Li Zhao (4 shared papers)Yiqing Wang (4 shared papers)Shuang Wang (3 shared papers)Jiang Yu (2 shared papers)Huanan Wang (2 shared papers)Minhui Yang (3 shared papers)Yanqing Ding (2 shared papers)Shasha Hu (3 shared papers)
- Journals
- Frontiers in Immunology (2 papers)Journal of Cellular and Molecular Medicine (2 papers)Carcinogenesis (1 paper)International Journal of Radiation Oncology*Biology*Physics (1 paper)Cell Death and Disease (1 paper)
- Partner nations
- ChinaUnited States
In The Last Decade
Mei-Ling Ai
14 papers receiving 504 citations
Peers
Comparison fields: 5 of 61
- Cancer Research 282
- Molecular Biology 370
- Oncology 97
- Immunology 67
- Epidemiology 75
Countries citing papers authored by Mei-Ling Ai
This map shows the geographic impact of Mei-Ling Ai'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 Mei-Ling Ai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mei-Ling Ai more than expected).
Fields of papers citing papers by Mei-Ling Ai
This network shows the impact of papers produced by Mei-Ling Ai. 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 Mei-Ling Ai. The network helps show where Mei-Ling Ai may publish in the future.
Co-authors
The 25 scholars most cited alongside Mei-Ling Ai, 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 | 2018 | 83 | |
| 2 | 2019 | 82 | |
| 3 | 2017 | 80 | |
| 4 | 2019 | 74 | |
| 5 | 2021 | 42 | |
| 6 | 2022 | 38 | |
| 7 | 2022 | 29 | |
| 8 | 2023 | 24 | |
| 9 | 2020 | 17 | |
| 10 | 2020 | 15 | |
| 11 | 2021 | 10 | |
| 12 | 2023 | 5 | |
| 13 | 2024 | 3 | |
| 14 | 2024 | 3 |
About Mei-Ling Ai
Mei-Ling Ai is a scholar working on Cancer Research, Oncology, Molecular Biology, Pathology and Forensic Medicine and Immunology, having authored 14 papers that have together received 505 indexed citations. Recurring topics across this work include Cancer-related molecular mechanisms research (7 papers), RNA modifications and cancer (3 papers), MicroRNA in disease regulation (2 papers), Peptidase Inhibition and Analysis (2 papers), Genetic factors in colorectal cancer (2 papers), RNA Research and Splicing (2 papers), Circular RNAs in diseases (2 papers) and Ubiquitin and proteasome pathways (2 papers). The work is most often cited by research in Cancer Research (282 citations), Molecular Biology (370 citations), Oncology (97 citations), Immunology (67 citations) and Epidemiology (75 citations). Mei-Ling Ai has collaborated with scholars based in China and United States. Frequent co-authors include Li Zhao, Yiqing Wang, Shuang Wang, Jiang Yu, Huanan Wang, Minhui Yang, Yanqing Ding, Shasha Hu, Lan Wang and Huijuan Jiang. Their work appears in journals such as Frontiers in Immunology, Journal of Cellular and Molecular Medicine, Carcinogenesis, International Journal of Radiation Oncology*Biology*Physics and Cell Death and Disease.
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.