Shanshan Wu
Impact in
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- Neurogenesis and neuroplasticity mechanisms
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- Neuroscience and Neural Engineering
Papers in
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- Pluripotent Stem Cells Research 5
- Single-cell and spatial transcriptomics 2
- RNA Research and Splicing 2
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- Neuroscience and Neural Engineering 3
- Genetic Neurodegenerative Diseases 2
- Co-authors
- Yuan Hong (7 shared papers)Xing Guo (6 shared papers)Mengdan Tao (6 shared papers)Min Xu (7 shared papers)Hao Hu (2 shared papers)Yan Liu (1 shared paper)Chu Chu (1 shared paper)Da Wang (2 shared papers)
- Journals
- Energies (1 paper)Scientific Reports (1 paper)Medicine (1 paper)EMBO Molecular Medicine (1 paper)ACS Nano (1 paper)
- Partner nations
- ChinaSouth KoreaIndia
In The Last Decade
Shanshan Wu
14 papers receiving 411 citations
Shanshan Wu's Hit Papers
Peers
Comparison fields: 5 of 81
- Developmental Neuroscience 25
- Cellular and Molecular Neuroscience 65
- Biomedical Engineering 149
- Molecular Biology 213
- Aging 5
Countries citing papers authored by Shanshan Wu
This map shows the geographic impact of Shanshan Wu'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 Shanshan Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shanshan Wu more than expected).
Fields of papers citing papers by Shanshan Wu
This network shows the impact of papers produced by Shanshan Wu. 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 Shanshan Wu. The network helps show where Shanshan Wu may publish in the future.
Co-authors
The 25 scholars most cited alongside Shanshan Wu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Human organoids in basic research and clinical applications Hit paper breakdown → | 2022 | 278 |
| 2 | 2022 | 49 | |
| 3 | 2024 | 24 | |
| 4 | 2024 | 17 | |
| 5 | 2022 | 16 | |
| 6 | 2024 | 8 | |
| 7 | 2024 | 7 | |
| 8 | 2024 | 5 | |
| 9 | 2023 | 4 | |
| 10 | 2021 | 3 | |
| 11 | 2025 | 1 | |
| 12 | 2024 | 1 | |
| 13 | 2025 | 1 | |
| 14 | 2023 | 1 | |
| 15 | 2025 | 0 | |
| 16 | 2024 | 0 |
About Shanshan Wu
Shanshan Wu is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience, Biomedical Engineering, Neurology and Physiology, having authored 16 papers that have together received 415 indexed citations. Recurring topics across this work include Pluripotent Stem Cells Research (5 papers), Neuroscience and Neural Engineering (3 papers), Single-cell and spatial transcriptomics (2 papers), RNA Research and Splicing (2 papers), Neurological disorders and treatments (2 papers), Genetic Neurodegenerative Diseases (2 papers), 3D Printing in Biomedical Research (2 papers) and Diet, Metabolism, and Disease (1 paper). The work is most often cited by research in Developmental Neuroscience (25 citations), Cellular and Molecular Neuroscience (65 citations), Biomedical Engineering (149 citations), Molecular Biology (213 citations) and Aging (5 citations). Shanshan Wu has collaborated with scholars based in China, South Korea and India. Frequent co-authors include Yuan Hong, Xing Guo, Mengdan Tao, Min Xu, Hao Hu, Yan Liu, Chu Chu, Da Wang, Xiaoyan Tang and Yan Liu. Their work appears in journals such as Energies, Scientific Reports, Medicine, EMBO Molecular Medicine and ACS Nano.
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.