Da Song
Impact in
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- Neurogenesis and neuroplasticity mechanisms
Papers in ⓘ
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- Neuroinflammation and Neurodegeneration Mechanisms 4
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- Neuroscience and Neuropharmacology Research 6
- Photoreceptor and optogenetics research 5
- Co-authors
- Hong Qing (14 shared papers)Zhenzhen Quan (14 shared papers)Qinghu Yang (6 shared papers)Lixun Zhang (15 shared papers)Zhen Xie (4 shared papers)Gaofeng Pan (1 shared paper)Jianping An (1 shared paper)Shuai Wang (1 shared paper)
In The Last Decade
Da Song
57 papers receiving 469 citations
Peers
Comparison fields: 5 of 100
- Biological Psychiatry 18
- Developmental Neuroscience 29
- Neurology 54
- Cellular and Molecular Neuroscience 107
- Sensory Systems 17
Countries citing papers authored by Da Song
This map shows the geographic impact of Da Song'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 Da Song with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Da Song more than expected).
Fields of papers citing papers by Da Song
This network shows the impact of papers produced by Da Song. 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 Da Song. The network helps show where Da Song may publish in the future.
Co-authors
The 25 scholars most cited alongside Da Song, 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 61 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 46 | |
| 2 | 2023 | 42 | |
| 3 | 2018 | 26 | |
| 4 | 2019 | 26 | |
| 5 | 2014 | 25 | |
| 6 | 2021 | 23 | |
| 7 | 2022 | 23 | |
| 8 | 2021 | 21 | |
| 9 | 2023 | 17 | |
| 10 | 2017 | 15 | |
| 11 | 2021 | 14 | |
| 12 | 2018 | 13 | |
| 13 | 2023 | 12 | |
| 14 | 2023 | 9 | |
| 15 | 2023 | 9 | |
| 16 | 2025 | 9 | |
| 17 | 2013 | 9 | |
| 18 | 2021 | 9 | |
| 19 | 2021 | 8 | |
| 20 | 2022 | 7 |
About Da Song
Da Song is a scholar working on Neurology, Cellular and Molecular Neuroscience, Behavioral Neuroscience, Mechanical Engineering and Developmental Neuroscience, having authored 61 papers that have together received 478 indexed citations. Recurring topics across this work include Robotic Mechanisms and Dynamics (6 papers), Neuroscience and Neuropharmacology Research (6 papers), Prosthetics and Rehabilitation Robotics (5 papers), Memory and Neural Mechanisms (5 papers), Cellular and Composite Structures (5 papers), Soft Robotics and Applications (5 papers), Photoreceptor and optogenetics research (5 papers) and Neuroinflammation and Neurodegeneration Mechanisms (4 papers). The work is most often cited by research in Biological Psychiatry (18 citations), Developmental Neuroscience (29 citations), Neurology (54 citations), Cellular and Molecular Neuroscience (107 citations) and Sensory Systems (17 citations). Da Song has collaborated with scholars based in China, Vietnam and Hong Kong. Frequent co-authors include Hong Qing, Zhenzhen Quan, Qinghu Yang, Lixun Zhang, Zhen Xie, Gaofeng Pan, Jianping An, Shuai Wang, Chunjian Wang and Juan Zhao. Their work appears in journals such as Robotica, Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science, Neuroscience & Biobehavioral Reviews, Journal of Energy Storage and Mechanical sciences.
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.