Jay Newby
Impact in
-
- stochastic dynamics and bifurcation
- Advanced Thermodynamics and Statistical Mechanics
- Mathematical Physics top 5%
- Stochastic processes and statistical mechanics
Papers in
-
- Diffusion and Search Dynamics 14
- Gene Regulatory Network Analysis 7
- RNA Research and Splicing 5
- Glycosylation and Glycoproteins Research 3
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- stochastic dynamics and bifurcation 18
- Co-authors
- Paul C. Bressloff (12 shared papers)M. Gregory Forest (12 shared papers)Samuel K. Lai (11 shared papers)James P. Keener (3 shared papers)Alison Schaefer (5 shared papers)Amy S. Gladfelter (6 shared papers)Kelsey Gasior (4 shared papers)Feifei Xu (3 shared papers)
- Journals
- Physical Review Letters (4 papers)Physical review. E (3 papers)Physical Biology (2 papers)Bulletin of Mathematical Biology (2 papers)Molecular Biology of the Cell (2 papers)
- Partner nations
- United StatesCanadaUnited Kingdom
In The Last Decade
Jay Newby
42 papers receiving 1.7k citations
Jay Newby's Hit Papers
Peers
Comparison fields: 5 of 129
- Statistical and Nonlinear Physics 437
- Mathematical Physics 174
- Biophysics 108
- Molecular Biology 1.0k
- Modeling and Simulation 66
Countries citing papers authored by Jay Newby
This map shows the geographic impact of Jay Newby'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 Jay Newby with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jay Newby more than expected).
Fields of papers citing papers by Jay Newby
This network shows the impact of papers produced by Jay Newby. 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 Jay Newby. The network helps show where Jay Newby may publish in the future.
Co-authors
The 25 scholars most cited alongside Jay Newby, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 44 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Stochastic models of intracellular transport Hit paper breakdown → | 2013 | 425 |
| 2 | HSP70 chaperones RNA-free TDP-43 into anisotropic intranuclear liquid spherical shells Hit paper breakdown → | 2021 | 228 |
| 3 | 2016 | 186 | |
| 4 | 2018 | 139 | |
| 5 | 2010 | 65 | |
| 6 | 2017 | 47 | |
| 7 | 2014 | 46 | |
| 8 | 2013 | 37 | |
| 9 | 2009 | 36 | |
| 10 | 2011 | 31 | |
| 11 | 2015 | 31 | |
| 12 | 2010 | 28 | |
| 13 | 2018 | 27 | |
| 14 | 2011 | 27 | |
| 15 | 2017 | 26 | |
| 16 | 2019 | 25 | |
| 17 | 2009 | 25 | |
| 18 | 2019 | 24 | |
| 19 | 2020 | 24 | |
| 20 | 2011 | 24 |
About Jay Newby
Jay Newby is a scholar working on Molecular Biology, Statistical and Nonlinear Physics, Mathematical Physics, Pharmaceutical Science and Cognitive Neuroscience, having authored 44 papers that have together received 1.7k indexed citations. Recurring topics across this work include stochastic dynamics and bifurcation (18 papers), Diffusion and Search Dynamics (14 papers), Stochastic processes and statistical mechanics (8 papers), Gene Regulatory Network Analysis (7 papers), RNA Research and Splicing (5 papers), Neural dynamics and brain function (4 papers), Advanced Drug Delivery Systems (4 papers) and Glycosylation and Glycoproteins Research (3 papers). The work is most often cited by research in Statistical and Nonlinear Physics (437 citations), Mathematical Physics (174 citations), Biophysics (108 citations), Molecular Biology (1.0k citations) and Modeling and Simulation (66 citations). Jay Newby has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Paul C. Bressloff, M. Gregory Forest, Samuel K. Lai, James P. Keener, Alison Schaefer, Amy S. Gladfelter, Kelsey Gasior, Feifei Xu, Lei Miao and C. Michael Lin. Their work appears in journals such as Physical Review Letters, Physical review. E, Physical Biology, Bulletin of Mathematical Biology and Molecular Biology of the Cell.
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.