Mengdi Wang
Impact in
- Developmental Neuroscience top 2%
- Neurogenesis and neuroplasticity mechanisms
- Neurology top 5%
- Neuroinflammation and Neurodegeneration Mechanisms
Papers in
-
- Single-cell and spatial transcriptomics 12
- Pluripotent Stem Cells Research 3
- RNA Research and Splicing 3
- Co-authors
- Xiaoqun Wang (18 shared papers)Qian Wu (14 shared papers)Le Sun (5 shared papers)Suijuan Zhong (8 shared papers)Yingchao Shi (6 shared papers)Ruiguo Chen (2 shared papers)Ai Fang (1 shared paper)Lijie Guo (1 shared paper)
- Journals
- Cell Research (2 papers)Nature Communications (2 papers)Protein & Cell (1 paper)Cell (1 paper)Nucleic Acids Research (1 paper)
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Mengdi Wang
31 papers receiving 1.1k citations
Mengdi Wang's Hit Papers
Peers
Comparison fields: 5 of 128
- Developmental Neuroscience 215
- Neurology 120
- Cellular and Molecular Neuroscience 152
- Molecular Biology 544
- Biophysics 28
Countries citing papers authored by Mengdi Wang
This map shows the geographic impact of Mengdi Wang'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 Mengdi Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mengdi Wang more than expected).
Fields of papers citing papers by Mengdi Wang
This network shows the impact of papers produced by Mengdi Wang. 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 Mengdi Wang. The network helps show where Mengdi Wang may publish in the future.
Co-authors
The 25 scholars most cited alongside Mengdi Wang, 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 32 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Vascularized human cortical organoids (vOrganoids) model cortical development in vivo Hit paper breakdown → | 2020 | 297 |
| 2 | 2021 | 97 | |
| 3 | 2020 | 95 | |
| 4 | 2022 | 77 | |
| 5 | 2021 | 72 | |
| 6 | 2021 | 55 | |
| 7 | 2019 | 47 | |
| 8 | 2021 | 34 | |
| 9 | 2021 | 34 | |
| 10 | 2021 | 33 | |
| 11 | 2022 | 32 | |
| 12 | 2023 | 22 | |
| 13 | 2021 | 21 | |
| 14 | 2019 | 20 | |
| 15 | 2018 | 18 | |
| 16 | 2024 | 17 | |
| 17 | 2024 | 17 | |
| 18 | 2023 | 15 | |
| 19 | 2023 | 15 | |
| 20 | 2023 | 15 |
About Mengdi Wang
Mengdi Wang is a scholar working on Molecular Biology, Cognitive Neuroscience, Neurology, Developmental Neuroscience and Immunology, having authored 32 papers that have together received 1.1k indexed citations. Recurring topics across this work include Single-cell and spatial transcriptomics (12 papers), Neurogenesis and neuroplasticity mechanisms (4 papers), Neuroinflammation and Neurodegeneration Mechanisms (4 papers), Immune cells in cancer (4 papers), Pluripotent Stem Cells Research (3 papers), RNA Research and Splicing (3 papers), Genetics and Neurodevelopmental Disorders (2 papers) and Organic Electronics and Photovoltaics (2 papers). The work is most often cited by research in Developmental Neuroscience (215 citations), Neurology (120 citations), Cellular and Molecular Neuroscience (152 citations), Molecular Biology (544 citations) and Biophysics (28 citations). Mengdi Wang has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Xiaoqun Wang, Qian Wu, Le Sun, Suijuan Zhong, Yingchao Shi, Ruiguo Chen, Ai Fang, Lijie Guo, Peng Li and Woo‐Ping Ge. Their work appears in journals such as Cell Research, Nature Communications, Protein & Cell, Cell and Nucleic Acids Research.
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.