John M. Bekkers

6.5k citations
56 papers · 5.1k indexed · 2 hit papers · h-index 31
Topics
Neuroscience and Neuropharmacology Research (34 papers)Neural dynamics and brain function (29 papers)Neuroscience and Neural Engineering (17 papers)

In The Last Decade

John M. Bekkers

56 papers receiving 5.1k citations

Hit Papers

Presynaptic mechanism for long-term potentiation in the h...198920262001201319901989100200300400500

Peers

John M. Bekkers
Comparison fields: 5 of 111
  • Cellular and Molecular Neuroscience 4.2k
  • Molecular Biology 2.2k
  • Cognitive Neuroscience 2.1k
  • Sensory Systems 676
  • Cell Biology 441
Replace Huizhong W. Tao with:
Huizhong W. Tao United States
Ian D. Forsythe United Kingdom
Boris Barbour France
Gilad Silberberg Sweden
Johan F. Storm Norway
Laurence O. Trussell United States
Isabel Llano France
Shaul Hestrin United States
Thomas S. Otis United States
Darrell A. Henze United States
John M. Bekkers relative to Huizhong W. Tao United States Huizhong W. Tao's profile →
Citations per field
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Huizhong W. Tao · 1×
Citations per year

Countries citing papers authored by John M. Bekkers

Since Specialization
Citations

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

Fields of papers citing papers by John M. Bekkers

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John M. Bekkers. 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 John M. Bekkers. The network helps show where John M. Bekkers may publish in the future.

Co-authorship network of co-authors of John M. Bekkers

This figure shows the co-authorship network connecting the top 25 collaborators of John M. Bekkers. A scholar is included among the top collaborators of John M. Bekkers based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with John M. Bekkers. John M. Bekkers is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 5
2 22
3 150
4 75
5 78
6 17
7 44
8 43
9 88
10 80
11 151
12 97
13 23
14 52
15 333
16 136
17 16
18 23
19 23
20
NMDA and non-NMDA receptors are co-localized at individual excitatory synapses in cultured rat hippocampusbreakdown →
568

About John M. Bekkers

John M. Bekkers is a scholar working on Cellular and Molecular Neuroscience, Sensory Systems and Cognitive Neuroscience, having authored 56 papers that have together received 5.1k indexed citations. Recurring topics across this work include Neuroscience and Neuropharmacology Research (34 papers), Neural dynamics and brain function (29 papers) and Neuroscience and Neural Engineering (17 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (4.2k citations), Sensory Systems (676 citations) and Cognitive Neuroscience (2.1k citations). John M. Bekkers has collaborated with scholars based in Australia, United States and Japan. Frequent co-authors include Charles F. Stevens, John D. Clements, Norimitsu Suzuki, George B. Richerson, Christopher A. Reid, Pankaj Sah, Andrew Delaney, Kaori Ikeda, Michael Häusser and Nikolaus G. Greeff. Their work appears in journals such as Nature, Science and Proceedings of the National Academy of Sciences.

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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