Jay T. Groves

197 papers receiving 12.8k citations

Peers

Jay T. Groves
Comparison fields: 5 of 150
  • Biophysics 921
  • Cell Biology 2.3k
  • Immunology and Allergy 762
  • Molecular Biology 8.6k
  • Immunology 2.0k
Replace Barbara A. Baird with:
Barbara A. Baird United States
Katharina Gaus Australia
Takahiro K Fujiwara Japan
Jacob Piehler Germany
Gerhard J. Schuetz Austria
Maddy Parsons United Kingdom
Kurt Anderson United Kingdom
Ken P. Ritchie United States
Kenichi G. N. Suzuki Japan
Alan Rick Horwitz United States
Jay T. Groves relative to Barbara A. Baird United States Barbara A. Baird's profile →
Citations per field
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Citations per year

Countries citing papers authored by Jay T. Groves

Since Specialization
Citations

This map shows the geographic impact of Jay T. Groves'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 T. Groves with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jay T. Groves more than expected).

Fields of papers citing papers by Jay T. Groves

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jay T. Groves. 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 T. Groves. The network helps show where Jay T. Groves may publish in the future.

Co-authors

The 25 scholars most cited alongside Jay T. Groves, 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 T. Groves Line = papers co-authored together Jay T. Groves links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 200 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2009532
2 1997515
3 2005444
4 2013399
5 2018348
6 2002311
7 2010288
8 2001286
9 2019278
10 1996276
11 2010249
12 2010242
13 2018231
14 2006219
15 2008218
16 2011205
17 2003203
18 2004190
19 2012188
20 2008180

About Jay T. Groves

Jay T. Groves is a scholar working on Cell Biology, Molecular Biology, Biophysics, Immunology and Atomic and Molecular Physics, and Optics, having authored 200 papers that have together received 13.1k indexed citations. Recurring topics across this work include Lipid Membrane Structure and Behavior (90 papers), Force Microscopy Techniques and Applications (28 papers), T-cell and B-cell Immunology (27 papers), Cellular transport and secretion (24 papers), Advanced Fluorescence Microscopy Techniques (21 papers), Nanopore and Nanochannel Transport Studies (20 papers), Immune Cell Function and Interaction (19 papers) and Cellular Mechanics and Interactions (18 papers). The work is most often cited by research in Biophysics (921 citations), Cell Biology (2.3k citations), Immunology and Allergy (762 citations), Molecular Biology (8.6k citations) and Immunology (2.0k citations). Jay T. Groves has collaborated with scholars based in United States, Singapore and China. Frequent co-authors include Steven G. Boxer, Michael Loran Dustin, John Kuriyan, Raghuveer Parthasarathy, Martin B. Forstner, Kaspar D. Mossman, Carolyn Ruth Bertozzi, Cheng‐han Yu, Arup K. Chakraborty and Jeffrey A. Nye. Their work appears in journals such as Biophysical Journal, Proceedings of the National Academy of Sciences, Langmuir, Journal of the American Chemical Society and The Journal of Physical Chemistry B.

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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