Weida Shen
Impact in
- Neurology top 5%
- Neuroinflammation and Neurodegeneration Mechanisms
- Physiology top 5%
- Adenosine and Purinergic Signaling
Papers in
-
- Neuroscience and Neuropharmacology Research 15
- Neurology 13
- Neuroinflammation and Neurodegeneration Mechanisms 13
- Co-authors
- Joshua L. Hertz (12 shared papers)Ljiljana Nikolić (5 shared papers)Étienne Audinat (5 shared papers)Paola Nobili (4 shared papers)Jun Jiang (3 shared papers)Linghui Zeng (11 shared papers)Chaoying Ni (2 shared papers)Jun Jiang (5 shared papers)
- Journals
- Glia (3 papers)Solid State Ionics (2 papers)Neurobiology of Disease (2 papers)Journal of Electroceramics (2 papers)Scientific Reports (1 paper)
- Partner nations
- ChinaUnited StatesFrance
In The Last Decade
Weida Shen
34 papers receiving 600 citations
Peers
Comparison fields: 5 of 86
- Neurology 164
- Physiology 72
- Cellular and Molecular Neuroscience 202
- Biological Psychiatry 20
- Developmental Neuroscience 22
Countries citing papers authored by Weida Shen
This map shows the geographic impact of Weida Shen'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 Weida Shen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Weida Shen more than expected).
Fields of papers citing papers by Weida Shen
This network shows the impact of papers produced by Weida Shen. 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 Weida Shen. The network helps show where Weida Shen may publish in the future.
Co-authors
The 25 scholars most cited alongside Weida Shen, 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 35 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 63 | |
| 2 | 2013 | 61 | |
| 3 | 2017 | 59 | |
| 4 | 2019 | 40 | |
| 5 | 2022 | 38 | |
| 6 | 2021 | 36 | |
| 7 | 2014 | 22 | |
| 8 | 2012 | 21 | |
| 9 | 2013 | 20 | |
| 10 | 2023 | 20 | |
| 11 | 2013 | 20 | |
| 12 | 2022 | 19 | |
| 13 | 2014 | 19 | |
| 14 | 2022 | 18 | |
| 15 | 2022 | 16 | |
| 16 | 2017 | 16 | |
| 17 | 2021 | 15 | |
| 18 | 2022 | 14 | |
| 19 | 2021 | 10 | |
| 20 | 2020 | 10 |
About Weida Shen
Weida Shen is a scholar working on Cellular and Molecular Neuroscience, Neurology, Materials Chemistry, Electronic, Optical and Magnetic Materials and Electrical and Electronic Engineering, having authored 35 papers that have together received 604 indexed citations. Recurring topics across this work include Neuroscience and Neuropharmacology Research (15 papers), Neuroinflammation and Neurodegeneration Mechanisms (13 papers), Advancements in Solid Oxide Fuel Cells (11 papers), Electronic and Structural Properties of Oxides (10 papers), Magnetic and transport properties of perovskites and related materials (8 papers), Memory and Neural Mechanisms (5 papers), Adenosine and Purinergic Signaling (4 papers) and Semiconductor materials and devices (3 papers). The work is most often cited by research in Neurology (164 citations), Physiology (72 citations), Cellular and Molecular Neuroscience (202 citations), Biological Psychiatry (20 citations) and Developmental Neuroscience (22 citations). Weida Shen has collaborated with scholars based in China, United States and France. Frequent co-authors include Joshua L. Hertz, Ljiljana Nikolić, Étienne Audinat, Paola Nobili, Jun Jiang, Linghui Zeng, Chaoying Ni, Jun Jiang, Frank W. Pfrieger and Lauriane Ulmann. Their work appears in journals such as Glia, Solid State Ionics, Neurobiology of Disease, Journal of Electroceramics and Scientific Reports.
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.