Aiping Li
Impact in
- Cancer Research top 5%
- Cancer-related molecular mechanisms research
- MicroRNA in disease regulation
- Molecular Biology top 5%
- Circular RNAs in diseases
- Ubiquitin and proteasome pathways
- RNA modifications and cancer
- DNA Repair Mechanisms
Papers in
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- Retinoids in leukemia and cellular processes 13
-
- Topic Modeling 25
- Advanced Graph Neural Networks 20
- Co-authors
- Jianwei Zhou (70 shared papers)Rong Jiang (17 shared papers)Yan Jia (17 shared papers)Yan Jia (2 shared papers)Jian Ye (5 shared papers)Jianbing Zhang (7 shared papers)Yansu Chen (6 shared papers)Song He (6 shared papers)
- Journals
- Journal of Toxicology and Environmental Health (7 papers)World Wide Web (4 papers)Scientific Reports (3 papers)IEEE Access (3 papers)Journal of Gastroenterology (2 papers)
- Partner nations
- ChinaUnited StatesNorway
In The Last Decade
Aiping Li
249 papers receiving 3.6k citations
Peers
Comparison fields: 5 of 194
- Cancer Research 575
- Molecular Biology 1.5k
- Oncology 468
- Artificial Intelligence 471
- Information Systems 306
Countries citing papers authored by Aiping Li
This map shows the geographic impact of Aiping 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 Aiping Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Aiping Li more than expected).
Fields of papers citing papers by Aiping Li
This network shows the impact of papers produced by Aiping 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 Aiping Li. The network helps show where Aiping Li may publish in the future.
Co-authors
The 25 scholars most cited alongside Aiping 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 267 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 157 | |
| 2 | 2018 | 122 | |
| 3 | 2019 | 116 | |
| 4 | 2012 | 102 | |
| 5 | 2012 | 100 | |
| 6 | 2016 | 70 | |
| 7 | 2017 | 69 | |
| 8 | 2007 | 66 | |
| 9 | 2018 | 61 | |
| 10 | 2016 | 60 | |
| 11 | 2009 | 60 | |
| 12 | 2020 | 60 | |
| 13 | 2007 | 57 | |
| 14 | 2019 | 53 | |
| 15 | 2013 | 50 | |
| 16 | 2018 | 50 | |
| 17 | 2013 | 49 | |
| 18 | 2020 | 46 | |
| 19 | 2008 | 45 | |
| 20 | 2006 | 42 |
About Aiping Li
Aiping Li is a scholar working on Molecular Biology, Artificial Intelligence, Computer Networks and Communications, Information Systems and Oncology, having authored 267 papers that have together received 3.7k indexed citations. Recurring topics across this work include Topic Modeling (25 papers), Advanced Graph Neural Networks (20 papers), Network Security and Intrusion Detection (16 papers), Retinoids in leukemia and cellular processes (13 papers), Manufacturing Process and Optimization (12 papers), Data Quality and Management (11 papers), Rough Sets and Fuzzy Logic (10 papers) and Complex Network Analysis Techniques (9 papers). The work is most often cited by research in Cancer Research (575 citations), Molecular Biology (1.5k citations), Oncology (468 citations), Artificial Intelligence (471 citations) and Information Systems (306 citations). Aiping Li has collaborated with scholars based in China, United States and Norway. Frequent co-authors include Jianwei Zhou, Rong Jiang, Yan Jia, Yan Jia, Jian Ye, Jianbing Zhang, Yansu Chen, Song He, Shudong Li and Shouyu Wang. Their work appears in journals such as Journal of Toxicology and Environmental Health, World Wide Web, Scientific Reports, IEEE Access and Journal of Gastroenterology.
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.