Michael C. Brown

157 papers receiving 8.0k citations

Michael C. Brown's Hit Papers

Paxillin: Adapting to Change 2004 · 531 citations
5310+16+33Years since publication200400600

Peers

Michael C. Brown
Comparison fields: 5 of 143
  • Immunology and Allergy 1.5k
  • Developmental Neuroscience 694
  • Cell Biology 2.0k
  • Cellular and Molecular Neuroscience 2.2k
  • Neurology 481
Replace R. Blake Pepinsky with:
R. Blake Pepinsky United States
A Hall United States
David Edgar United Kingdom
Klaus Addicks Germany
Anthony J. Koleske United States
Cord Brakebusch Denmark
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Kazumasa Ohashi Japan
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Citations per field
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Citations per year

Countries citing papers authored by Michael C. Brown

Since Specialization
Citations

This map shows the geographic impact of Michael C. Brown'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 Michael C. Brown with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael C. Brown more than expected).

Fields of papers citing papers by Michael C. Brown

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael C. Brown. 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 Michael C. Brown. The network helps show where Michael C. Brown may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 160 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Polyneuronal innervation of skeletal muscle in new‐born rats and its elimination during maturation.
Hit paper breakdown →
1976658
2
Paxillin: Adapting to Change
Hit paper breakdown →
2004531
3
Motor Nerve Sprouting
Hit paper breakdown →
1981443
4 1999410
5 1996314
6 1978272
7 1991266
8 2017183
9 1998155
10 2005153
11 1989148
12 1990147
13 2001145
14 2002144
15 1998122
16 1991120
17 1991117
18 2001112
19 1998108
20 1992105

About Michael C. Brown

Michael C. Brown is a scholar working on Molecular Biology, Immunology, Cell Biology, Oncology and Immunology and Allergy, having authored 160 papers that have together received 8.3k indexed citations. Recurring topics across this work include Cell Adhesion Molecules Research (24 papers), Cellular Mechanics and Interactions (18 papers), Virus-based gene therapy research (16 papers), interferon and immune responses (14 papers), Monoclonal and Polyclonal Antibodies Research (14 papers), Glycosylation and Glycoproteins Research (13 papers), Immunotherapy and Immune Responses (13 papers) and CAR-T cell therapy research (13 papers). The work is most often cited by research in Immunology and Allergy (1.5k citations), Developmental Neuroscience (694 citations), Cell Biology (2.0k citations), Cellular and Molecular Neuroscience (2.2k citations) and Neurology (481 citations). Michael C. Brown has collaborated with scholars based in United States, United Kingdom and Germany. Frequent co-authors include Christopher E. Turner, V. Hugh Perry, Will G. Hopkins, Jan Jansen, David C. Van Essen, Joseph A. Perrotta, R. L. Holland, Matthias Gromeier, E. R. Lunn and R Ironton. Their work appears in journals such as Neuro-Oncology, European Journal of Neuroscience, Proceedings of the National Academy of Sciences, The Journal of Immunology and Journal of Biological Chemistry.

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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