Raffaele Calabretta

33 total papers · 600 total citations
19 papers, 252 citations indexed

About

Raffaele Calabretta is a scholar working on Molecular Biology, Artificial Intelligence and Sociology and Political Science. According to data from OpenAlex, Raffaele Calabretta has authored 19 papers receiving a total of 252 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 5 papers in Artificial Intelligence and 4 papers in Sociology and Political Science. Recurrent topics in Raffaele Calabretta's work include Evolution and Genetic Dynamics (4 papers), Evolutionary Game Theory and Cooperation (4 papers) and Peptidase Inhibition and Analysis (3 papers). Raffaele Calabretta is often cited by papers focused on Evolution and Genetic Dynamics (4 papers), Evolutionary Game Theory and Cooperation (4 papers) and Peptidase Inhibition and Analysis (3 papers). Raffaele Calabretta collaborates with scholars based in Italy, United States and United Kingdom. Raffaele Calabretta's co-authors include Domenico Parisi, Günter P. Wagner, Stefano Nolfi, Cesare Giordano, Carlo Gallina, Andrea Di Ferdinando, Valerio Consalvi, Mark Klein, Paolo Spada and Luca Iandoli and has published in prestigious journals such as Philosophical Transactions of the Royal Society B Biological Sciences, European Journal of Medicinal Chemistry and Synthesis.

In The Last Decade

Raffaele Calabretta

18 papers receiving 237 citations

Author Peers

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

Author						Papers	Cites
Raffaele Calabretta	91	71	34	33	29	19	252
Joseph P. Dexter	38 0.4×	89 1.3×	4 0.1×	21 0.6×	21 0.7×	19	225
Woojin Kim	57 0.6×	134 1.9×	16 0.5×	4 0.1×	6 0.2×	22	309
Garima Gupta	22 0.2×	18 0.3×	76 2.2×	23 0.7×	13 0.4×	20	219
R. Clyde White	34 0.4×	115 1.6×	8 0.2×	4 0.1×	15 0.5×	18	276
Yukio Gunji	21 0.2×	46 0.6×	7 0.2×	30 0.9×	17 0.6×	33	245
Bernd‐Olaf Küppers	17 0.2×	88 1.2×	4 0.1×	23 0.7×	40 1.4×	12	234
Nathanaël Aubert-Kato	37 0.4×	130 1.8×	3 0.1×	14 0.4×	7 0.2×	26	254
Yu‐Jen Chen	14 0.2×	78 1.1×	35 1.0×	26 0.8×	25 0.9×	22	324
Patrick Amar	7 0.1×	196 2.8×	15 0.4×	6 0.2×	6 0.2×	22	309
Ya Zhang	9 0.1×	112 1.6×	12 0.4×	9 0.3×	56 1.9×	15	308

Countries citing papers authored by Raffaele Calabretta

Since Specialization

Citations

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

Fields of papers citing papers by Raffaele Calabretta

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Raffaele Calabretta

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