Mario Barbieri

1.8k citations
48 papers · 1.4k · h-index 17

Impact in

Papers in

Mario Barbieri

46 papers receiving 1.3k citations

Peers

Mario Barbieri
Comparison fields: 5 of 85
  • Sensory Systems 275
  • Cellular and Molecular Neuroscience 453
  • Cardiology and Cardiovascular Medicine 392
  • Toxicology 60
  • Physiology 246
Replace Mircea Iftinca with:
Mircea Iftinca Canada
Hayato Matsuyama Japan
Edda Adler‐Graschinsky Argentina
Péter Sántha Hungary
Ian McFadzean United Kingdom
Keiichi Omote Japan
Barbara Malinowska Poland
Vittorio Vellani Italy
Sendoa Tajada United States
Jooyoung Jung South Korea
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Citations per field
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Citations per year

Countries citing papers authored by Mario Barbieri

Since Specialization
Citations

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

Fields of papers citing papers by Mario Barbieri

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 48 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2002358
2 1994144
3 1996118
4 1994100
5 200366
6 199448
7 201643
8 199543
9 200243
10 201937
11 201835
12 200833
13 199430
14 200128
15 200925
16 200924
17 200521
18 201313
19 202213
20 202113

About Mario Barbieri

Mario Barbieri is a scholar working on Cellular and Molecular Neuroscience, Molecular Biology, Cardiology and Cardiovascular Medicine, Physiology and Pharmacology, having authored 48 papers that have together received 1.4k indexed citations. Recurring topics across this work include Neuroscience and Neuropharmacology Research (15 papers), Cardiac electrophysiology and arrhythmias (10 papers), Receptor Mechanisms and Signaling (7 papers), Ion channel regulation and function (7 papers), Neuropeptides and Animal Physiology (6 papers), Neurogenesis and neuroplasticity mechanisms (5 papers), Cannabis and Cannabinoid Research (5 papers) and Pain Mechanisms and Treatments (5 papers). The work is most often cited by research in Sensory Systems (275 citations), Cellular and Molecular Neuroscience (453 citations), Cardiology and Cardiovascular Medicine (392 citations), Toxicology (60 citations) and Physiology (246 citations). Mario Barbieri has collaborated with scholars based in Italy, United States and United Kingdom. Frequent co-authors include Alessandro Mugelli, Elisabetta Cerbai, Qi Li, Michele Simonato, Jeffrey C. Jerman, Stephen Brough, Marcello Trevisani, Davina E. OWEN, Andrew D. Randall and Silvia Amadesi. Their work appears in journals such as Journal of Visualized Experiments, British Journal of Pharmacology, Neuropharmacology, Pharmacological Research and 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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