Shiming Tang
Impact in
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- Neurobiology and Insect Physiology Research
- Neuroscience and Neural Engineering
- Photoreceptor and optogenetics research
- Cognitive Neuroscience top 5%
- Neural dynamics and brain function
- Visual perception and processing mechanisms
Papers in
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- Advanced Fluorescence Microscopy Techniques 7
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- Visual perception and processing mechanisms 18
- Neural dynamics and brain function 18
- Co-authors
- Aike GuoMing LiMikko JuusolaYing WangHongfei JiangFang LiuTai Sing LeeNiansheng Ju
- Journals
- Progress in Neurobiology (4 papers)Science (4 papers)Nature Communications (3 papers)Journal of Cleaner Production (3 papers)eLife (3 papers)
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Shiming Tang
58 papers receiving 1.5k citations
Peers
Comparison fields: 5 of 149
- Cellular and Molecular Neuroscience 577
- Cognitive Neuroscience 542
- Soil Science 117
- Biophysics 56
- Ecology, Evolution, Behavior and Systematics 168
Countries citing papers authored by Shiming Tang
This map shows the geographic impact of Shiming Tang'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 Shiming Tang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shiming Tang more than expected).
Fields of papers citing papers by Shiming Tang
This network shows the impact of papers produced by Shiming Tang. 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 Shiming Tang. The network helps show where Shiming Tang may publish in the future.
Co-authors
The 25 scholars most cited alongside Shiming Tang, 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 | 2025 | 0 | |
| 2 | 2025 | 0 | |
| 3 | 2024 | 3 | |
| 4 | 2024 | 3 | |
| 5 | 2023 | 12 | |
| 6 | 2023 | 1 | |
| 7 | 2022 | 21 | |
| 8 | 2022 | 11 | |
| 9 | 2021 | 25 | |
| 10 | 2021 | 9 | |
| 11 | 2021 | 7 | |
| 12 | 2020 | 12 | |
| 13 | 2020 | 39 | |
| 14 | 2019 | 17 | |
| 15 | 2018 | 161 | |
| 16 | Effects of artificial lakes on moisture, electrical conductivity and pH of adjacent soil on degraded grassland. | 2018 | 1 |
| 17 | 2018 | 22 | |
| 18 | 2016 | 57 | |
| 19 | 2010 | 42 | |
| 20 | 2004 | 60 |
About Shiming Tang
Shiming Tang is a scholar working on Biophysics, Cognitive Neuroscience, Soil Science, Cellular and Molecular Neuroscience and Ecology, having authored 65 papers that have together received 1.5k indexed citations. Recurring topics across this work include Visual perception and processing mechanisms (18 papers), Neural dynamics and brain function (18 papers), Soil Carbon and Nitrogen Dynamics (11 papers), Retinal Development and Disorders (8 papers), Advanced Fluorescence Microscopy Techniques (7 papers), Neurobiology and Insect Physiology Research (6 papers), COVID-19 and Mental Health (4 papers) and Child Nutrition and Feeding Issues (3 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (577 citations), Cognitive Neuroscience (542 citations), Soil Science (117 citations), Biophysics (56 citations) and Ecology, Evolution, Behavior and Systematics (168 citations). Shiming Tang has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Aike Guo, Ming Li, Mikko Juusola, Ying Wang, Hongfei Jiang, Fang Liu, Tai Sing Lee, Niansheng Ju, Zhongchun Liu and Reinhard Wolf. Their work appears in journals such as Progress in Neurobiology, Science, Nature Communications, Journal of Cleaner Production and eLife.
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.