Sheila Nirenberg
- Cognitive Neuroscience top 1%
- Neural dynamics and brain function 20
- Visual perception and processing mechanisms 7
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- Photoreceptor and optogenetics research 14
- Neuroscience and Neural Engineering 13
- Neuroscience and Neuropharmacology Research 5
- Sensory Systems top 5%
- Molecular Biology top 10%
- Retinal Development and Disorders 19
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- Neural Networks and Applications 3
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- Advanced Memory and Neural Computing 3
- Co-authors
- Peter E. LathamMarkus MeisterChethan PandarinathStephen CarcieriBarry J. RichmondP. G. NelsonAdam JacobsYanshu Wang
- Journals
- Journal of Neuroscience (5 papers)Journal of Neurophysiology (4 papers)Proceedings of the National Academy of Sciences (3 papers)
- Partner nations
- United StatesUnited KingdomCanada
In The Last Decade
Sheila Nirenberg
33 papers receiving 2.0k citations
Peers
Comparison fields: 5 of 88
- Cognitive Neuroscience 1.4k
- Cellular and Molecular Neuroscience 1.3k
- Statistical and Nonlinear Physics 297
- Sensory Systems 63
- Molecular Biology 840
Countries citing papers authored by Sheila Nirenberg
This map shows the geographic impact of Sheila Nirenberg'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 Sheila Nirenberg with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sheila Nirenberg more than expected).
Fields of papers citing papers by Sheila Nirenberg
This network shows the impact of papers produced by Sheila Nirenberg. 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 Sheila Nirenberg. The network helps show where Sheila Nirenberg may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Sheila Nirenberg, 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 | 2023 | 15 | |
| 2 | 2023 | 2 | |
| 3 | 2016 | 22 | |
| 4 | 2016 | 18 | |
| 5 | 2013 | 9 | |
| 6 | 2012 | 13 | |
| 7 | 2010 | 48 | |
| 8 | 2010 | 7 | |
| 9 | 2009 | 128 | |
| 10 | 2009 | 117 | |
| 11 | 2007 | 23 | |
| 12 | 2005 | 152 | |
| 13 | 2005 | 2 | |
| 14 | 2004 | 43 | |
| 15 | 2001 | 223 | |
| 16 | 2001 | 30 | |
| 17 | 2000 | 227 | |
| 18 | 1998 | 29 | |
| 19 | 1998 | 234 | |
| 20 | 1997 | 108 |
About Sheila Nirenberg
Sheila Nirenberg is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Molecular Biology, having authored 33 papers that have together received 2.1k indexed citations. Recurring topics across this work include Neural dynamics and brain function (20 papers), Retinal Development and Disorders (19 papers), Photoreceptor and optogenetics research (14 papers), Neuroscience and Neural Engineering (13 papers), Visual perception and processing mechanisms (7 papers), Neuroscience and Neuropharmacology Research (5 papers), Neural Networks and Applications (3 papers) and Advanced Memory and Neural Computing (3 papers). The work is most often cited by research in Cognitive Neuroscience (1.4k citations), Cellular and Molecular Neuroscience (1.3k citations) and Statistical and Nonlinear Physics (297 citations). Sheila Nirenberg has collaborated with scholars based in United States, United Kingdom and Canada. Frequent co-authors include Peter E. Latham, Markus Meister, Chethan Pandarinath, Stephen Carcieri, Barry J. Richmond, P. G. Nelson, Adam Jacobs, Yanshu Wang, Jeremy Nathans and Jonathan D. Victor. Their work appears in journals such as Journal of Neuroscience, Journal of Neurophysiology, Proceedings of the National Academy of Sciences, Journal of Vision and Current Opinion in Neurobiology.
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.