Mei-Ling Ai

752 citations
14 papers · 526 · h-index 11

Impact in

    • Cancer-related molecular mechanisms research
    • MicroRNA in disease regulation
    • RNA modifications and cancer
    • Circular RNAs in diseases
    • RNA Research and Splicing

Papers in

    • RNA modifications and cancer 2
    • RNA Research and Splicing 2
    • Cancer-related molecular mechanisms research 6
    • MicroRNA in disease regulation 2

Mei-Ling Ai

14 papers receiving 526 citations

Peers

Mei-Ling Ai
Comparison fields: 5 of 57
  • Cancer Research 255
  • Molecular Biology 315
  • Oncology 86
  • Immunology 52
  • Epidemiology 65
Replace S Chen with:
S Chen China
Xinwen Zhong China
Dianke Chen China
Nicole P. Ho Hong Kong
Lang Fang China
Yuntan Qiu China
Maopeng Yang China
Huanye Mo China
Yanmei Cui China
Zhonghai Guan China
Mei-Ling Ai relative to S Chen China S Chen's profile →
Citations per field
00.5×
S Chen · 1×
Citations per year

Countries citing papers authored by Mei-Ling Ai

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

Border = papers with Mei-Ling Ai Line = papers co-authored together Mei-Ling Ai links everyone, so they are left out of the graph.

All Works

14 of 14 papers shown
#Work
1 201886
2 201983
3 201781
4 201974
5 202144
6 202241
7 202232
8 202329
9 202017
10 202016
11 202111
12 20235
13 20244
14 20243

About Mei-Ling Ai

Mei-Ling Ai is a scholar working on Molecular Biology, Cancer Research, Oncology, Pathology and Forensic Medicine and Epidemiology, having authored 14 papers that have together received 526 indexed citations. Recurring topics across this work include Cancer-related molecular mechanisms research (6 papers), Peptidase Inhibition and Analysis (2 papers), MicroRNA in disease regulation (2 papers), Genetic factors in colorectal cancer (2 papers), RNA modifications and cancer (2 papers), RNA Research and Splicing (2 papers), Advanced Proteomics Techniques and Applications (1 paper) and Pancreatic and Hepatic Oncology Research (1 paper). The work is most often cited by research in Cancer Research (255 citations), Molecular Biology (315 citations), Oncology (86 citations), Immunology (52 citations) and Epidemiology (65 citations). Mei-Ling Ai has collaborated with scholars based in China and United States. Frequent co-authors include Li Zhao, Yiqing Wang, Shuang Wang, Huanan Wang, Jiang Yu, Yue Han, Yanqing Ding, Huijuan Jiang, Lan Wang and Shasha Hu. Their work appears in journals such as Frontiers in Immunology, Journal of Cellular and Molecular Medicine, International Journal of Biological Sciences, Molecular Cancer and Oncogene.

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.

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