Jay Newby

2.5k citations
43 papers · 1.7k · 2 hit papers · h-index 23

Impact in

Papers in

Jay Newby

42 papers receiving 1.6k citations

Jay Newby's Hit Papers

HSP70 chaperones RNA-free TDP-43 into anisotropic intranuclear liquid spherical shells 2021 · 218 citations
2180+4+8Years since publication100200300400

Peers

Jay Newby
Comparison fields: 5 of 128
  • Statistical and Nonlinear Physics 428
  • Mathematical Physics 171
  • Biophysics 109
  • Molecular Biology 1.0k
  • Modeling and Simulation 63
Replace Anatoly B. Kolomeisky with:
Anatoly B. Kolomeisky United States
Amitabha Nandi India
Ramon Grima United Kingdom
Stephanie C. Weber United States
Ioan Kosztin United States
Juan Elezgaray France
Gernot Guigas Germany
Bartłomiej Waclaw United Kingdom
Jeroen S. van Zon Netherlands
Ariel Amir United States
Jay Newby relative to Anatoly B. Kolomeisky United States Anatoly B. Kolomeisky's profile →
Citations per field
00.5×1.5×2.2×
Anatoly B. Kolomeisky · 1×
Citations per year

Countries citing papers authored by Jay Newby

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

Border = papers with Jay Newby Line = papers co-authored together Jay Newby links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 43 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Stochastic models of intracellular transport
Hit paper breakdown →
2013420
2
HSP70 chaperones RNA-free TDP-43 into anisotropic intranuclear liquid spherical shells
Hit paper breakdown →
2021218
3 2016179
4 2018132
5 201064
6 201446
7 201743
8 201337
9 200935
10 201531
11 201130
12 201027
13 201826
14 201126
15 201925
16 201725
17 200925
18 201924
19 202024
20 201323

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 43 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 (428 citations), Mathematical Physics (171 citations), Biophysics (109 citations), Molecular Biology (1.0k citations) and Modeling and Simulation (63 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, Lu Zhang and Matthew I. Milowsky. Their work appears in journals such as Physical Review Letters, Physical review. E, Physical Biology, Molecular Biology of the Cell and Bulletin of Mathematical Biology.

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.

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