Huling Li
Impact in
- Modeling and Simulation top 2%
- COVID-19 epidemiological studies
- Health Information Management top 10%
- Artificial Intelligence in Healthcare
Papers in
-
- Neuroscience and Neuropharmacology Research 3
- Neuropeptides and Animal Physiology 3
- Co-authors
- Kai Wang (6 shared papers)Zhihang Peng (3 shared papers)Hua Yao (1 shared paper)Zhan‐Wei Suo (6 shared papers)Xiao‐Dong Hu (6 shared papers)Zhen Guo (6 shared papers)Xian Yang (5 shared papers)He Huang (1 shared paper)
- Journals
- European Journal of Pharmacology (2 papers)Frontiers in Genetics (1 paper)Mathematical Biosciences & Engineering (1 paper)Journal of the American College of Cardiology (1 paper)Acta Pharmaceutica Sinica B (1 paper)
- Partner nations
- ChinaHong KongNetherlands
In The Last Decade
Huling Li
26 papers receiving 379 citations
Peers
Comparison fields: 5 of 97
- Modeling and Simulation 101
- Health Information Management 21
- Infectious Diseases 49
- Cellular and Molecular Neuroscience 38
- Physiology 44
Countries citing papers authored by Huling Li
This map shows the geographic impact of Huling 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 Huling Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Huling Li more than expected).
Fields of papers citing papers by Huling Li
This network shows the impact of papers produced by Huling 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 Huling Li. The network helps show where Huling Li may publish in the future.
Co-authors
The 25 scholars most cited alongside Huling 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 27 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 63 | |
| 2 | 2020 | 41 | |
| 3 | 2020 | 32 | |
| 4 | 2020 | 32 | |
| 5 | 2018 | 27 | |
| 6 | 2020 | 21 | |
| 7 | 2019 | 20 | |
| 8 | 2023 | 18 | |
| 9 | 2022 | 18 | |
| 10 | 2019 | 18 | |
| 11 | 2022 | 13 | |
| 12 | 2020 | 13 | |
| 13 | 2009 | 13 | |
| 14 | 2021 | 11 | |
| 15 | 2020 | 10 | |
| 16 | 2023 | 8 | |
| 17 | 2020 | 6 | |
| 18 | 2018 | 5 | |
| 19 | 2025 | 4 | |
| 20 | 2022 | 4 |
About Huling Li
Huling Li is a scholar working on Cellular and Molecular Neuroscience, Molecular Biology, Epidemiology, Physiology and Modeling and Simulation, having authored 27 papers that have together received 393 indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (4 papers), Pain Mechanisms and Treatments (4 papers), Neuroscience and Neuropharmacology Research (3 papers), COVID-19 Pandemic Impacts (3 papers), Neuropeptides and Animal Physiology (3 papers), Ferroptosis and cancer prognosis (2 papers), SARS-CoV-2 and COVID-19 Research (2 papers) and Artificial Intelligence in Healthcare (2 papers). The work is most often cited by research in Modeling and Simulation (101 citations), Health Information Management (21 citations), Infectious Diseases (49 citations), Cellular and Molecular Neuroscience (38 citations) and Physiology (44 citations). Huling Li has collaborated with scholars based in China, Hong Kong and Netherlands. Frequent co-authors include Kai Wang, Zhihang Peng, Hua Yao, Zhan‐Wei Suo, Xiao‐Dong Hu, Zhen Guo, Xian Yang, He Huang, Lixing Zhang and Wenjing Zhao. Their work appears in journals such as European Journal of Pharmacology, Frontiers in Genetics, Mathematical Biosciences & Engineering, Journal of the American College of Cardiology and Acta Pharmaceutica Sinica B.
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.