Fake Li
Impact in
- Infectious Diseases top 5%
- Tuberculosis Research and Epidemiology
- Reproductive Medicine top 10%
- Ovarian cancer diagnosis and treatment
Papers in
-
- Advanced biosensing and bioanalysis techniques 3
- Epigenetics and DNA Methylation 2
-
- Tuberculosis Research and Epidemiology 4
- Co-authors
- Shaoli Deng (11 shared papers)Kai Chang (11 shared papers)Shuangrong Jia (9 shared papers)Kejun Zhang (6 shared papers)Weiping Lu (4 shared papers)Ming Chen (5 shared papers)Junji Wang (1 shared paper)Lili Yu (2 shared papers)
- Journals
- Biosensors and Bioelectronics (3 papers)Frontiers in Genetics (3 papers)Journal of Infection (2 papers)Biochemical and Biophysical Research Communications (1 paper)Journal of Clinical Microbiology (1 paper)
- Partner nations
- ChinaUnited States
In The Last Decade
Fake Li
19 papers receiving 695 citations
Peers
Comparison fields: 5 of 78
- Infectious Diseases 273
- Reproductive Medicine 83
- Epidemiology 149
- Bioengineering 25
- Cancer Research 53
Countries citing papers authored by Fake Li
This map shows the geographic impact of Fake 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 Fake Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fake Li more than expected).
Fields of papers citing papers by Fake Li
This network shows the impact of papers produced by Fake 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 Fake Li. The network helps show where Fake Li may publish in the future.
Co-authors
The 25 scholars most cited alongside Fake 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
| # | Work | ||
|---|---|---|---|
| 1 | 2012 | 205 | |
| 2 | 2014 | 101 | |
| 3 | 2012 | 99 | |
| 4 | 2015 | 78 | |
| 5 | 2018 | 39 | |
| 6 | 2013 | 37 | |
| 7 | 2011 | 28 | |
| 8 | 2013 | 19 | |
| 9 | 2012 | 18 | |
| 10 | 2020 | 18 | |
| 11 | 2012 | 13 | |
| 12 | 2023 | 13 | |
| 13 | 2022 | 11 | |
| 14 | 2021 | 9 | |
| 15 | 2013 | 9 | |
| 16 | 2019 | 7 | |
| 17 | 2023 | 3 | |
| 18 | 2022 | 3 | |
| 19 | 2020 | 2 |
About Fake Li
Fake Li is a scholar working on Molecular Biology, Infectious Diseases, Biomedical Engineering, Genetics and Epidemiology, having authored 19 papers that have together received 712 indexed citations. Recurring topics across this work include Tuberculosis Research and Epidemiology (4 papers), Biosensors and Analytical Detection (3 papers), Genomics and Rare Diseases (3 papers), Advanced biosensing and bioanalysis techniques (3 papers), Genetics and Neurodevelopmental Disorders (2 papers), Epigenetics and DNA Methylation (2 papers), Acoustic Wave Resonator Technologies (2 papers) and Hepatitis B Virus Studies (1 paper). The work is most often cited by research in Infectious Diseases (273 citations), Reproductive Medicine (83 citations), Epidemiology (149 citations), Bioengineering (25 citations) and Cancer Research (53 citations). Fake Li has collaborated with scholars based in China and United States. Frequent co-authors include Shaoli Deng, Kai Chang, Shuangrong Jia, Kejun Zhang, Weiping Lu, Ming Chen, Junji Wang, Lili Yu, Jianfeng Shi and Weiping Lu. Their work appears in journals such as Biosensors and Bioelectronics, Frontiers in Genetics, Journal of Infection, Biochemical and Biophysical Research Communications and Journal of Clinical Microbiology.
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.