Fabio Cavaliere

64 total papers · 2.7k total citations
45 papers, 2.2k citations indexed

About

Fabio Cavaliere is a scholar working on Cellular and Molecular Neuroscience, Physiology and Developmental Neuroscience. According to data from OpenAlex, Fabio Cavaliere has authored 45 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Cellular and Molecular Neuroscience, 20 papers in Physiology and 14 papers in Developmental Neuroscience. Recurrent topics in Fabio Cavaliere's work include Adenosine and Purinergic Signaling (20 papers), Neurogenesis and neuroplasticity mechanisms (14 papers) and Neuroscience and Neuropharmacology Research (9 papers). Fabio Cavaliere is often cited by papers focused on Adenosine and Purinergic Signaling (20 papers), Neurogenesis and neuroplasticity mechanisms (14 papers) and Neuroscience and Neuropharmacology Research (9 papers). Fabio Cavaliere collaborates with scholars based in Spain, Italy and Germany. Fabio Cavaliere's co-authors include Carlos Matute, Cinzia Volonté, Giorgio Bernardi, Nadia D’Ambrosi, Susanna Amadio, Giuseppe Sancesario, Elena Alberdi, Marı́a Victoria Sánchez-Gómez, Alberto Pérez-Samartı́n and José L. Zugaza and has published in prestigious journals such as The Journal of Immunology, PLoS ONE and Neuroscience.

In The Last Decade

Fabio Cavaliere

43 papers receiving 2.1k citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Fabio Cavaliere 859 690 605 579 520 45 2.2k
Karl Asmund Rudolphi 880 1.0× 984 1.4× 724 1.2× 597 1.0× 463 0.9× 43 2.8k
Alberto Pérez-Samartı́n 633 0.7× 969 1.4× 921 1.5× 876 1.5× 414 0.8× 50 2.9k
Ariel R. Ase 554 0.6× 1.0k 1.5× 829 1.4× 320 0.6× 501 1.0× 57 2.2k
Rosa Gómez‐Villafuertes 1.3k 1.5× 525 0.8× 702 1.2× 328 0.6× 286 0.6× 59 2.2k
Hai‐Ying Shen 806 0.9× 788 1.1× 929 1.5× 399 0.7× 196 0.4× 58 2.6k
Elisabetta Coppi 665 0.8× 558 0.8× 713 1.2× 617 1.1× 541 1.0× 87 2.4k
Zhenghua Xiang 1.2k 1.4× 459 0.7× 755 1.2× 599 1.0× 434 0.8× 84 2.9k
Jinmin Zhu 674 0.8× 1.4k 2.0× 1.7k 2.8× 490 0.8× 332 0.6× 42 3.1k
Lane K. Bekar 315 0.4× 1.3k 1.8× 932 1.5× 896 1.5× 576 1.1× 39 3.2k
Fiona E. Parkinson 1.4k 1.6× 854 1.2× 704 1.2× 444 0.8× 232 0.4× 73 2.6k

Countries citing papers authored by Fabio Cavaliere

Since Specialization
Citations

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

Fields of papers citing papers by Fabio Cavaliere

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fabio Cavaliere

This figure shows the co-authorship network connecting the top 25 collaborators of Fabio Cavaliere. A scholar is included among the top collaborators of Fabio Cavaliere 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 Fabio Cavaliere. Fabio Cavaliere is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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