Guangwei Si
Impact in
- Aging top 10%
-
- Neurobiology and Insect Physiology Research
Papers in
- Genetics 7
- Insect and Arachnid Ecology and Behavior 4
- Evolution and Genetic Dynamics 3
-
- Neurobiology and Insect Physiology Research 5
- Co-authors
- Aravinthan D. T. Samuel (5 shared papers)Li He (1 shared paper)Norbert Perrimon (1 shared paper)Jiuhong Huang (1 shared paper)Qi Ouyang (7 shared papers)Chunxiong Luo (6 shared papers)Yuhai Tu (5 shared papers)Luis Hernandez-Nunez (2 shared papers)
- Journals
- Physical Review Letters (4 papers)Proceedings of the National Academy of Sciences (2 papers)eLife (2 papers)Microelectronic Engineering (1 paper)Multiscale Modeling and Simulation (1 paper)
- Partner nations
- ChinaUnited StatesIndia
In The Last Decade
Guangwei Si
13 papers receiving 745 citations
Peers
Comparison fields: 5 of 88
- Aging 32
- Cellular and Molecular Neuroscience 307
- Sensory Systems 62
- Modeling and Simulation 47
- Cell Biology 105
Countries citing papers authored by Guangwei Si
This map shows the geographic impact of Guangwei Si'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 Guangwei Si with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Guangwei Si more than expected).
Fields of papers citing papers by Guangwei Si
This network shows the impact of papers produced by Guangwei Si. 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 Guangwei Si. The network helps show where Guangwei Si may publish in the future.
Co-authors
The 25 scholars most cited alongside Guangwei Si, 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 | 2018 | 244 | |
| 2 | 2016 | 135 | |
| 3 | 2015 | 66 | |
| 4 | 2019 | 55 | |
| 5 | 2012 | 52 | |
| 6 | 2012 | 40 | |
| 7 | 2012 | 37 | |
| 8 | 2013 | 37 | |
| 9 | 2020 | 31 | |
| 10 | 2019 | 23 | |
| 11 | 2017 | 14 | |
| 12 | 2014 | 14 | |
| 13 | 2025 | 2 | |
| 14 | 2009 | 1 |
About Guangwei Si
Guangwei Si is a scholar working on Genetics, Cellular and Molecular Neuroscience, Biomedical Engineering, Molecular Biology and Modeling and Simulation, having authored 14 papers that have together received 751 indexed citations. Recurring topics across this work include Neurobiology and Insect Physiology Research (5 papers), Insect and Arachnid Ecology and Behavior (4 papers), Mathematical Biology Tumor Growth (4 papers), Gene Regulatory Network Analysis (4 papers), Microfluidic and Bio-sensing Technologies (3 papers), Evolution and Genetic Dynamics (3 papers), Physiological and biochemical adaptations (2 papers) and Olfactory and Sensory Function Studies (2 papers). The work is most often cited by research in Aging (32 citations), Cellular and Molecular Neuroscience (307 citations), Sensory Systems (62 citations), Modeling and Simulation (47 citations) and Cell Biology (105 citations). Guangwei Si has collaborated with scholars based in China, United States and India. Frequent co-authors include Aravinthan D. T. Samuel, Li He, Norbert Perrimon, Jiuhong Huang, Qi Ouyang, Chunxiong Luo, Yuhai Tu, Luis Hernandez-Nunez, Christopher J. Tabone and Matthew Berck. Their work appears in journals such as Physical Review Letters, Proceedings of the National Academy of Sciences, eLife, Microelectronic Engineering and Multiscale Modeling and Simulation.
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.