Michael Seagar

86 papers receiving 3.0k citations

Peers

Michael Seagar
Comparison fields: 5 of 99
  • Cell Biology 1.2k
  • Cellular and Molecular Neuroscience 1.3k
  • Physiology 158
  • Molecular Biology 2.4k
  • Neurology 433
Replace Margaret H. Butler with:
Margaret H. Butler United States
Laurie Daniell United States
Manfred W. Kilimann Germany
R. A. Jeffrey McIlhinney United Kingdom
Robert Sealock United States
Alexander G. Petrenko Russia
Barbara Baryłko United States
Ling-Gang Wu United States
Makoto Itakura Japan
Weichun Lin United States
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Citations per field
00.5×2.7×
Margaret H. Butler · 1×
Citations per year

Countries citing papers authored by Michael Seagar

Since Specialization
Citations

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

Fields of papers citing papers by Michael Seagar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 87 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1987356
2 1994175
3 1988160
4 1996122
5 2010117
6 199589
7 200085
8 200084
9 199882
10 199774
11 201071
12 199069
13 199966
14 201765
15 199562
16 200159
17 201150
18 200248
19 199747
20 200046

About Michael Seagar

Michael Seagar is a scholar working on Molecular Biology, Cell Biology, Cellular and Molecular Neuroscience, Neurology and Genetics, having authored 87 papers that have together received 3.0k indexed citations. Recurring topics across this work include Cellular transport and secretion (43 papers), Ion channel regulation and function (40 papers), Lipid Membrane Structure and Behavior (24 papers), Nicotinic Acetylcholine Receptors Study (17 papers), Neuroscience and Neuropharmacology Research (17 papers), Botulinum Toxin and Related Neurological Disorders (10 papers), Myasthenia Gravis and Thymoma (10 papers) and Neurological disorders and treatments (8 papers). The work is most often cited by research in Cell Biology (1.2k citations), Cellular and Molecular Neuroscience (1.3k citations), Physiology (158 citations), Molecular Biology (2.4k citations) and Neurology (433 citations). Michael Seagar has collaborated with scholars based in France, Japan and United States. Frequent co-authors include Masami Takahashi, Christian Lévêque, William A. Catterall, Nicole Martin‐Moutôt, Béatrice Marquèze‐Pouey, Oussama El Far, Masayuki Takahashi, Cécile Iborra, B F Reber and James F. Jones. Their work appears in journals such as Journal of Biological Chemistry, Proceedings of the National Academy of Sciences, FEBS Letters, Annals of the New York Academy of Sciences and European Journal of Neuroscience.

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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