Mauro Provinciali

263 total papers · 6.6k total citations
194 papers, 4.8k citations indexed

About

Mauro Provinciali is a scholar working on Molecular Biology, Immunology and Physiology. According to data from OpenAlex, Mauro Provinciali has authored 194 papers receiving a total of 4.8k indexed citations (citations by other indexed papers that have themselves been cited), including 67 papers in Molecular Biology, 66 papers in Immunology and 21 papers in Physiology. Recurrent topics in Mauro Provinciali's work include Immune Cell Function and Interaction (32 papers), Immunotherapy and Immune Responses (26 papers) and T-cell and B-cell Immunology (21 papers). Mauro Provinciali is often cited by papers focused on Immune Cell Function and Interaction (32 papers), Immunotherapy and Immune Responses (26 papers) and T-cell and B-cell Immunology (21 papers). Mauro Provinciali collaborates with scholars based in Italy, United States and Poland. Mauro Provinciali's co-authors include Giuseppina Di Stefano, Ν. Fabris, Fiorenza Orlando, Alessia Donnini, Elisa Pierpaoli, Nicola Fabris, Francesca Re, Eugenio Mocchegiani, Beatrice Bartozzi and Mario Muzzioli and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Hepatology.

In The Last Decade

Mauro Provinciali

191 papers receiving 4.7k citations

Author Peers

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

Author Last Decade Papers Cites
Mauro Provinciali 1.5k 1.2k 601 585 461 194 4.8k
Lucia Malaguarnera 1.9k 1.3× 938 0.8× 633 1.1× 428 0.7× 337 0.7× 99 4.8k
Chiara Cerletti 1.4k 0.9× 978 0.8× 927 1.5× 650 1.1× 373 0.8× 294 8.5k
Nichole Reisdorph 1.9k 1.3× 1.1k 0.9× 905 1.5× 255 0.4× 254 0.6× 139 5.0k
Udai P. Singh 1.9k 1.3× 1.6k 1.3× 509 0.8× 1.0k 1.7× 193 0.4× 157 5.4k
Marie‐Paule Vasson 1.4k 0.9× 583 0.5× 1.6k 2.7× 721 1.2× 651 1.4× 130 4.9k
Chang Chen 3.1k 2.1× 846 0.7× 714 1.2× 403 0.7× 421 0.9× 240 6.1k
Na Wang 2.1k 1.4× 839 0.7× 534 0.9× 286 0.5× 154 0.3× 271 4.9k
Eunok Im 1.5k 1.0× 654 0.6× 369 0.6× 487 0.8× 252 0.5× 108 3.7k
Jacek M. Witkowski 1.6k 1.1× 2.2k 1.9× 1.6k 2.6× 572 1.0× 191 0.4× 183 6.7k
Andreas Simm 2.6k 1.8× 583 0.5× 958 1.6× 482 0.8× 268 0.6× 220 6.4k

Countries citing papers authored by Mauro Provinciali

Since Specialization
Citations

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

Fields of papers citing papers by Mauro Provinciali

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mauro Provinciali

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