Jinxia Dai
Impact in
- Biological Psychiatry top 10%
- Behavioral Neuroscience top 10%
- Stress Responses and Cortisol
Papers in
-
- Single-cell and spatial transcriptomics 3
- Retinal Development and Disorders 3
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- Neuroscience and Neuropharmacology Research 6
- Axon Guidance and Neuronal Signaling 3
- Co-authors
- Yu‐Qiang Ding (6 shared papers)Chao Guo (2 shared papers)Ming Shi (2 shared papers)Gang Cao (12 shared papers)Huili Han (2 shared papers)Jun Cao (1 shared paper)Ying Huang (2 shared papers)Ning‐Ning Song (2 shared papers)
- Journals
- Molecular and Cellular Neuroscience (2 papers)Veterinary Microbiology (2 papers)Nature Communications (1 paper)Neuroscience Research (1 paper)Microbial Pathogenesis (1 paper)
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Jinxia Dai
36 papers receiving 640 citations
Peers
Comparison fields: 5 of 101
- Biological Psychiatry 32
- Behavioral Neuroscience 42
- Developmental Neuroscience 43
- Cellular and Molecular Neuroscience 194
- Virology 28
Countries citing papers authored by Jinxia Dai
This map shows the geographic impact of Jinxia Dai'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 Jinxia Dai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jinxia Dai more than expected).
Fields of papers citing papers by Jinxia Dai
This network shows the impact of papers produced by Jinxia Dai. 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 Jinxia Dai. The network helps show where Jinxia Dai may publish in the future.
Co-authors
The 25 scholars most cited alongside Jinxia Dai, 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 37 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2008 | 120 | |
| 2 | 2019 | 59 | |
| 3 | 2008 | 57 | |
| 4 | 2019 | 55 | |
| 5 | 2023 | 37 | |
| 6 | 2016 | 34 | |
| 7 | 2023 | 32 | |
| 8 | 2009 | 31 | |
| 9 | 2021 | 29 | |
| 10 | 2008 | 21 | |
| 11 | 2013 | 16 | |
| 12 | 2017 | 15 | |
| 13 | 2021 | 14 | |
| 14 | 2022 | 13 | |
| 15 | 2020 | 13 | |
| 16 | 2012 | 12 | |
| 17 | 2021 | 11 | |
| 18 | 2023 | 11 | |
| 19 | 2019 | 10 | |
| 20 | 2014 | 10 |
About Jinxia Dai
Jinxia Dai is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience, Infectious Diseases, Cognitive Neuroscience and Epidemiology, having authored 37 papers that have together received 647 indexed citations. Recurring topics across this work include Neuroscience and Neuropharmacology Research (6 papers), Rabies epidemiology and control (4 papers), interferon and immune responses (4 papers), Single-cell and spatial transcriptomics (3 papers), Axon Guidance and Neuronal Signaling (3 papers), Viral Infections and Vectors (3 papers), Retinal Development and Disorders (3 papers) and Neural dynamics and brain function (3 papers). The work is most often cited by research in Biological Psychiatry (32 citations), Behavioral Neuroscience (42 citations), Developmental Neuroscience (43 citations), Cellular and Molecular Neuroscience (194 citations) and Virology (28 citations). Jinxia Dai has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Yu‐Qiang Ding, Chao Guo, Ming Shi, Gang Cao, Huili Han, Jun Cao, Ying Huang, Ning‐Ning Song, Tian‐Le Xu and Meng Tian. Their work appears in journals such as Molecular and Cellular Neuroscience, Veterinary Microbiology, Nature Communications, Neuroscience Research and Microbial Pathogenesis.
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.