Su Wang
Impact in
- Developmental Neuroscience top 0.2%
- Neurogenesis and neuroplasticity mechanisms
- Neurology top 1%
- Neuroinflammation and Neurodegeneration Mechanisms
Papers in
-
- Topic Modeling 6
- Natural Language Processing Techniques 5
- Co-authors
- Steven A. Goldman (15 shared papers)Maiken Nedergaard (7 shared papers)Abdellatif Benraiss (8 shared papers)Neeta S. Roy (5 shared papers)Richard A. R. Fraser (4 shared papers)Takahiro Takano (3 shared papers)Xiaoning Han (2 shared papers)Martha S. Windrem (3 shared papers)
- Journals
- Journal of Neuroscience (6 papers)PLoS ONE (3 papers)Cell Reports (2 papers)Journal of Biological Chemistry (2 papers)Annals of the New York Academy of Sciences (2 papers)
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Su Wang
118 papers receiving 4.3k citations
Su Wang's Hit Papers
Peers
Comparison fields: 5 of 189
- Developmental Neuroscience 1.1k
- Neurology 667
- Cellular and Molecular Neuroscience 1.1k
- Genetics 285
- Molecular Biology 1.8k
Countries citing papers authored by Su Wang
This map shows the geographic impact of Su 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 Su Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Su Wang more than expected).
Fields of papers citing papers by Su Wang
This network shows the impact of papers produced by Su 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 Su Wang. The network helps show where Su Wang may publish in the future.
Co-authors
The 25 scholars most cited alongside Su 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 125 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Forebrain Engraftment by Human Glial Progenitor Cells Enhances Synaptic Plasticity and Learning in Adult Mice Hit paper breakdown → | 2013 | 449 |
| 2 | 2000 | 434 | |
| 3 | 2007 | 384 | |
| 4 | 1999 | 198 | |
| 5 | 2007 | 170 | |
| 6 | 2016 | 145 | |
| 7 | 2000 | 142 | |
| 8 | 2008 | 132 | |
| 9 | 2014 | 118 | |
| 10 | 2019 | 109 | |
| 11 | 1998 | 103 | |
| 12 | 2014 | 102 | |
| 13 | 2015 | 94 | |
| 14 | 2018 | 91 | |
| 15 | 2016 | 76 | |
| 16 | 2013 | 67 | |
| 17 | 2022 | 66 | |
| 18 | 2023 | 66 | |
| 19 | 1998 | 64 | |
| 20 | 2005 | 57 |
About Su Wang
Su Wang is a scholar working on Molecular Biology, Artificial Intelligence, Computer Vision and Pattern Recognition, Cellular and Molecular Neuroscience and Radiology, Nuclear Medicine and Imaging, having authored 125 papers that have together received 4.4k indexed citations. Recurring topics across this work include Neurogenesis and neuroplasticity mechanisms (8 papers), Colorectal Cancer Screening and Detection (8 papers), Multimodal Machine Learning Applications (6 papers), Topic Modeling (6 papers), Natural Language Processing Techniques (5 papers), Glioma Diagnosis and Treatment (5 papers), Neuroscience and Neuropharmacology Research (5 papers) and Neuroinflammation and Neurodegeneration Mechanisms (5 papers). The work is most often cited by research in Developmental Neuroscience (1.1k citations), Neurology (667 citations), Cellular and Molecular Neuroscience (1.1k citations), Genetics (285 citations) and Molecular Biology (1.8k citations). Su Wang has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Steven A. Goldman, Maiken Nedergaard, Abdellatif Benraiss, Neeta S. Roy, Richard A. R. Fraser, Takahiro Takano, Xiaoning Han, Martha S. Windrem, William T. Couldwell and Ayano Kawaguchi. Their work appears in journals such as Journal of Neuroscience, PLoS ONE, Cell Reports, Journal of Biological Chemistry and Annals of the New York Academy of 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.