Shunit Gal-Ben-Ari

9 papers receiving 624 citations

Peers

Shunit Gal-Ben-Ari
Comparison fields: 5 of 82
  • Biological Psychiatry 31
  • Cellular and Molecular Neuroscience 225
  • Behavioral Neuroscience 19
  • Neurology 43
  • Sensory Systems 25
Replace Juliana M. Rosa with:
Juliana M. Rosa Spain
Casey L. Kilpatrick United States
Ayelet Katzoff Israel
Brett J.W. Teubner United States
Mitradas M. Panicker India
Samarjit Bhattacharyya India
Atsushi Tsujimura Japan
Svenja V. Trossbach Germany
Ana F. Oliveira Brazil
Nicole A. R. Walter United States
Shunit Gal-Ben-Ari relative to Juliana M. Rosa Spain Juliana M. Rosa's profile →
Citations per field
00.5×1.5×
Juliana M. Rosa · 1×
Citations per year

Countries citing papers authored by Shunit Gal-Ben-Ari

Since Specialization
Citations

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

Fields of papers citing papers by Shunit Gal-Ben-Ari

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shunit Gal-Ben-Ari. 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 Shunit Gal-Ben-Ari. The network helps show where Shunit Gal-Ben-Ari may publish in the future.

Co-authors

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

All Works

9 of 9 papers shown
#Work
1 2019190
2 2014129
3 201389
4 201270
5 201267
6 201140
7 202024
8 201614
9 20186

About Shunit Gal-Ben-Ari

Shunit Gal-Ben-Ari is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience, Cognitive Neuroscience, Cell Biology and Nutrition and Dietetics, having authored 9 papers that have together received 629 indexed citations. Recurring topics across this work include Neuroscience and Neuropharmacology Research (5 papers), Receptor Mechanisms and Signaling (3 papers), Biochemical Analysis and Sensing Techniques (2 papers), Memory and Neural Mechanisms (2 papers), RNA and protein synthesis mechanisms (2 papers), Genetics and Neurodevelopmental Disorders (1 paper), Cardiac electrophysiology and arrhythmias (1 paper) and Ion channel regulation and function (1 paper). The work is most often cited by research in Biological Psychiatry (31 citations), Cellular and Molecular Neuroscience (225 citations), Behavioral Neuroscience (19 citations), Neurology (43 citations) and Sensory Systems (25 citations). Shunit Gal-Ben-Ari has collaborated with scholars based in Israel, United Kingdom and Norway. Frequent co-authors include Kobi Rosenblum, Iliana Barrera, Marcelo Ehrlich, Tali Rosenberg, Michael R. Kreutz, Noam Ziv, Daniela C. Dieterich, Eckart D. Gundelfinger, Rachel Karry and Dorit Ben‐Shachar. Their work appears in journals such as Frontiers in Molecular Neuroscience, Neurobiology of Learning and Memory, npj Science of Learning, Learning & Memory and Frontiers in Behavioral 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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