Lijun Li
- Cellular and Molecular Neuroscience top 2%
- Molecular Biology
- Physiology top 10%
- Endocrine and Autonomic Systems top 2%
- Surgery
- Co-authors
- Zofia ŻukowskaEdward LeeJoanna KitlińskaMichael G. FehlingsLydia E. KuoJason U. TilanJennifer PonsMary Susan Burnett
- Topics
- Neuropeptides and Animal Physiology (7 papers)Nerve injury and regeneration (7 papers)Spinal Cord Injury Research (6 papers)
- Cited by
- Cellular and Molecular NeuroscienceDevelopmental NeuroscienceEndocrine and Autonomic Systems
- Journals
- Proceedings of the National Academy of SciencesJournal of Biological ChemistryNature Medicine
- Partner nations
- United StatesCanadaChina
In The Last Decade
Lijun Li
37 papers receiving 1.9k citations
Hit Papers
Peers
Comparison fields: 5 of 125
- Cellular and Molecular Neuroscience 878
- Molecular Biology 619
- Physiology 320
- Endocrine and Autonomic Systems 264
- Surgery 236
Countries citing papers authored by Lijun Li
This map shows the geographic impact of Lijun 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 Lijun Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lijun Li more than expected).
Fields of papers citing papers by Lijun Li
This network shows the impact of papers produced by Lijun 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 Lijun Li. The network helps show where Lijun Li may publish in the future.
Co-authorship network of co-authors of Lijun Li
This figure shows the co-authorship network connecting the top 25 collaborators of Lijun Li. A scholar is included among the top collaborators of Lijun Li based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Lijun Li. Lijun Li is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 4 | |
| 3 | 1 | |
| 4 | 5 | |
| 5 | 65 | |
| 6 | 27 | |
| 7 | 43 | |
| 8 | 19 | |
| 9 | 10 | |
| 10 | 84 | |
| 11 | 21 | |
| 12 | 4 | |
| 13 | 14 | |
| 14 | 37 | |
| 15 | 35 | |
| 16 | 32 | |
| 17 | 3 | |
| 18 | 10 | |
| 19 | 85 | |
| 20 | 108 |
About Lijun Li
Lijun Li is a scholar working on Cellular and Molecular Neuroscience, Developmental Neuroscience and Pathology and Forensic Medicine, having authored 39 papers that have together received 1.9k indexed citations. Recurring topics across this work include Neuropeptides and Animal Physiology (7 papers), Nerve injury and regeneration (7 papers) and Spinal Cord Injury Research (6 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (878 citations), Developmental Neuroscience (195 citations) and Endocrine and Autonomic Systems (264 citations). Lijun Li has collaborated with scholars based in United States, Canada and China. Frequent co-authors include Zofia Żukowska, Edward Lee, Joanna Kitlińska, Michael G. Fehlings, Lydia E. Kuo, Jason U. Tilan, Jennifer Pons, Mary Susan Burnett, Michael D. Johnson and Stephen B. Baker. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Nature Medicine.
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.