Frances K. Skinner
- Cellular and Molecular Neuroscience top 1%
- Cognitive Neuroscience top 1%
- Molecular Biology
- Statistical and Nonlinear Physics top 2%
- Computer Networks and Communications top 5%
- Co-authors
- Eve MarderLiang ZhangBrian MulloneyJosé Luis Pérez VelázquezPeter L. CarlenNancy KopellFernanda SaragaAndrew A. Sharp
- Topics
- Neural dynamics and brain function (68 papers)Neuroscience and Neuropharmacology Research (52 papers)Photoreceptor and optogenetics research (22 papers)
- Partner nations
- CanadaUnited StatesUnited Kingdom
In The Last Decade
Frances K. Skinner
86 papers receiving 1.9k citations
Peers
Comparison fields: 5 of 103
- Cellular and Molecular Neuroscience 1.4k
- Cognitive Neuroscience 1.3k
- Molecular Biology 445
- Statistical and Nonlinear Physics 359
- Computer Networks and Communications 200
Countries citing papers authored by Frances K. Skinner
This map shows the geographic impact of Frances K. Skinner'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 Frances K. Skinner with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Frances K. Skinner more than expected).
Fields of papers citing papers by Frances K. Skinner
This network shows the impact of papers produced by Frances K. Skinner. 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 Frances K. Skinner. The network helps show where Frances K. Skinner may publish in the future.
Co-authorship network of co-authors of Frances K. Skinner
This figure shows the co-authorship network connecting the top 25 collaborators of Frances K. Skinner. A scholar is included among the top collaborators of Frances K. Skinner based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Frances K. Skinner. Frances K. Skinner is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 2 | |
| 3 | 3 | |
| 4 | 32 | |
| 5 | 17 | |
| 6 | 39 | |
| 7 | 10 | |
| 8 | 12 | |
| 9 | 7 | |
| 10 | 23 | |
| 11 | 19 | |
| 12 | 2 | |
| 13 | 121 | |
| 14 | 28 | |
| 15 | 20 | |
| 16 | 1 | |
| 17 | 16 | |
| 18 | 76 | |
| 19 | 17 | |
| 20 | 193 |
About Frances K. Skinner
Frances K. Skinner is a scholar working on Cellular and Molecular Neuroscience, Cognitive Neuroscience and Statistical and Nonlinear Physics, having authored 86 papers that have together received 2.0k indexed citations. Recurring topics across this work include Neural dynamics and brain function (68 papers), Neuroscience and Neuropharmacology Research (52 papers) and Photoreceptor and optogenetics research (22 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (1.4k citations), Cognitive Neuroscience (1.3k citations) and Statistical and Nonlinear Physics (359 citations). Frances K. Skinner has collaborated with scholars based in Canada, United States and United Kingdom. Frequent co-authors include Eve Marder, Liang Zhang, Brian Mulloney, José Luis Pérez Velázquez, Peter L. Carlen, Nancy Kopell, Fernanda Saraga, Andrew A. Sharp, Chenggang Wu and Katie Ferguson. Their work appears in journals such as Journal of Neuroscience, PLoS ONE and The Journal of Physiology.
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.