Laura Cavalleri

42 total papers · 586 total citations
20 papers, 470 citations indexed

About

Laura Cavalleri is a scholar working on Cellular and Molecular Neuroscience, Molecular Biology and Pharmacology. According to data from OpenAlex, Laura Cavalleri has authored 20 papers receiving a total of 470 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Cellular and Molecular Neuroscience, 8 papers in Molecular Biology and 6 papers in Pharmacology. Recurrent topics in Laura Cavalleri's work include Neuroscience and Neuropharmacology Research (9 papers), Treatment of Major Depression (6 papers) and Neurotransmitter Receptor Influence on Behavior (5 papers). Laura Cavalleri is often cited by papers focused on Neuroscience and Neuropharmacology Research (9 papers), Treatment of Major Depression (6 papers) and Neurotransmitter Receptor Influence on Behavior (5 papers). Laura Cavalleri collaborates with scholars based in Italy, Switzerland and France. Laura Cavalleri's co-authors include Ginetta Collo, PierFranco Spano, Emilio Merlo Pich, Mark J. Millan, Cristiano Chiamulera, Tilo Kunath, Federica Bono, Laura Plebani, Cristina Missale and Giovanna Piovani and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Neurochemistry and Molecular Psychiatry.

In The Last Decade

Laura Cavalleri

20 papers receiving 468 citations

Author Peers

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

Author Last Decade Papers Cites
Laura Cavalleri 238 178 119 108 67 20 470
Sophie M. Banas 258 1.1× 173 1.0× 71 0.6× 64 0.6× 44 0.7× 16 476
Kaoru Seiriki 197 0.8× 154 0.9× 106 0.9× 97 0.9× 54 0.8× 29 407
Maria S. Quinton 296 1.2× 201 1.1× 87 0.7× 69 0.6× 41 0.6× 21 536
Federica Marmo 319 1.3× 227 1.3× 92 0.8× 85 0.8× 69 1.0× 18 548
Albert Ferrés‐Coy 277 1.2× 206 1.2× 65 0.5× 98 0.9× 52 0.8× 15 520
Daniela Bonini 171 0.7× 230 1.3× 59 0.5× 100 0.9× 40 0.6× 15 471
Joanna Miszkiel 289 1.2× 190 1.1× 128 1.1× 57 0.5× 56 0.8× 24 468
Akinwunmi Oni-Orisan 233 1.0× 114 0.6× 95 0.8× 128 1.2× 131 2.0× 10 494
David M. Otte 189 0.8× 192 1.1× 170 1.4× 57 0.5× 64 1.0× 16 492
Yun‐Fang Jia 167 0.7× 163 0.9× 49 0.4× 54 0.5× 63 0.9× 21 487

Countries citing papers authored by Laura Cavalleri

Since Specialization
Citations

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

Fields of papers citing papers by Laura Cavalleri

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Laura Cavalleri

This figure shows the co-authorship network connecting the top 25 collaborators of Laura Cavalleri. A scholar is included among the top collaborators of Laura Cavalleri 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 Laura Cavalleri. Laura Cavalleri 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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