Carson C. Chow
- Statistical and Nonlinear Physics top 0.2%
- stochastic dynamics and bifurcation 18
- Genetics top 0.1%
- Estrogen and related hormone effects 9
- Cognitive Neuroscience top 0.5%
- Neural dynamics and brain function 37
-
- Neuroscience and Neural Engineering 8
- Molecular Biology top 1%
- RNA Research and Splicing 11
-
- Nonlinear Dynamics and Pattern Formation 18
-
- Obesity, Physical Activity, Diet 9
-
- Advanced Memory and Neural Computing 8
- Co-authors
- Shashaank VattikutiJames J. LeeChristopher ChangShaun PurcellJames J. CollinsThomas T. ImhoffKevin D. HallCarlo R. Laing
- Journals
- Journal of Computational Neuroscience (5 papers)Physical Review Letters (5 papers)PLoS Computational Biology (5 papers)
- Partner nations
- United StatesChinaHong Kong
In The Last Decade
Carson C. Chow
147 papers receiving 14.6k citations
Hit Papers
Peers
Comparison fields: 5 of 207
- Statistical and Nonlinear Physics 2.2k
- Genetics 4.8k
- Cognitive Neuroscience 3.2k
- Cellular and Molecular Neuroscience 1.3k
- Molecular Biology 4.0k
Countries citing papers authored by Carson C. Chow
This map shows the geographic impact of Carson C. Chow'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 Carson C. Chow with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Carson C. Chow more than expected).
Fields of papers citing papers by Carson C. Chow
This network shows the impact of papers produced by Carson C. Chow. 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 Carson C. Chow. The network helps show where Carson C. Chow may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Carson C. Chow, 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 | 2024 | 3 | |
| 2 | 2021 | 4 | |
| 3 | 2021 | 11 | |
| 4 | 2020 | 49 | |
| 5 | 2016 | 5 | |
| 6 | Second-generation PLINK: rising to the challenge of larger and richer datasetsbreakdown → | 2015 | 6558 |
| 7 | 2015 | 92 | |
| 8 | 2014 | 161 | |
| 9 | 2014 | 1 | |
| 10 | 2013 | 230 | |
| 11 | 2012 | 4 | |
| 12 | 2011 | 34 | |
| 13 | 2011 | 9 | |
| 14 | 2010 | 22 | |
| 15 | 2009 | 77 | |
| 16 | 2005 | 117 | |
| 17 | 2005 | 41 | |
| 18 | 2002 | 258 | |
| 19 | Spike-frequency adaptation improves noise-shaping in model neuronal networks | 2000 | 0 |
| 20 | 1996 | 257 |
About Carson C. Chow
Carson C. Chow is a scholar working on Cognitive Neuroscience, Statistical and Nonlinear Physics and Modeling and Simulation, having authored 151 papers that have together received 14.9k indexed citations. Recurring topics across this work include Neural dynamics and brain function (37 papers), Nonlinear Dynamics and Pattern Formation (18 papers), stochastic dynamics and bifurcation (18 papers), RNA Research and Splicing (11 papers), Obesity, Physical Activity, Diet (9 papers), Estrogen and related hormone effects (9 papers), Advanced Memory and Neural Computing (8 papers) and Neuroscience and Neural Engineering (8 papers). The work is most often cited by research in Statistical and Nonlinear Physics (2.2k citations), Genetics (4.8k citations) and Cognitive Neuroscience (3.2k citations). Carson C. Chow has collaborated with scholars based in United States, China and Hong Kong. Frequent co-authors include Shashaank Vattikuti, James J. Lee, Christopher Chang, Shaun Purcell, James J. Collins, Thomas T. Imhoff, Kevin D. Hall, Carlo R. Laing, John A. White and Juen Guo. Their work appears in journals such as Journal of Computational Neuroscience, Physical Review Letters, PLoS Computational Biology, eLife and PLoS ONE.
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.