Etrusca D’Urbano

9 total papers · 713 total citations
9 papers, 612 citations indexed

About

Etrusca D’Urbano is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Nutrition and Dietetics. According to data from OpenAlex, Etrusca D’Urbano has authored 9 papers receiving a total of 612 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 3 papers in Cellular and Molecular Neuroscience and 3 papers in Nutrition and Dietetics. Recurrent topics in Etrusca D’Urbano's work include Receptor Mechanisms and Signaling (4 papers), Protein Kinase Regulation and GTPase Signaling (3 papers) and Eicosanoids and Hypertension Pharmacology (3 papers). Etrusca D’Urbano is often cited by papers focused on Receptor Mechanisms and Signaling (4 papers), Protein Kinase Regulation and GTPase Signaling (3 papers) and Eicosanoids and Hypertension Pharmacology (3 papers). Etrusca D’Urbano collaborates with scholars based in Italy, United States and Spain. Etrusca D’Urbano's co-authors include Michele Sallese, Antonio De Blasi, Stefania Mariggiò, Luisa Iacovelli, Mario Romano, Giovanni Davı̀, Sebastiano Gangemi, Lorena Salvatore, Marianna Storto and Gianluca Sala and has published in prestigious journals such as Journal of the American College of Cardiology, The FASEB Journal and Journal of Applied Physiology.

In The Last Decade

Etrusca D’Urbano

9 papers receiving 593 citations

Author Peers

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

Author						Papers	Cites
Etrusca D’Urbano	395	227	76	72	72	9	612
Beat Flühmann	526 1.3×	165 0.7×	62 0.8×	22 0.3×	45 0.6×	8	647
E M Subers	413 1.0×	283 1.2×	121 1.6×	42 0.6×	87 1.2×	13	691
Daniel Vial	250 0.6×	93 0.4×	38 0.5×	31 0.4×	39 0.5×	14	578
Cesaria Prontera	169 0.4×	127 0.6×	213 2.8×	44 0.6×	82 1.1×	10	676
Edward B. Seguin	386 1.0×	93 0.4×	41 0.5×	49 0.7×	74 1.0×	12	669
Véronique Juvin	390 1.0×	78 0.3×	23 0.3×	72 1.0×	47 0.7×	9	653
Eckhard Bender	390 1.0×	179 0.8×	34 0.4×	28 0.4×	18 0.3×	12	582
P. Pettis	268 0.7×	112 0.5×	30 0.4×	33 0.5×	32 0.4×	14	524
Michiyo Okutani	427 1.1×	86 0.4×	29 0.4×	25 0.3×	52 0.7×	6	582
Rudi Prihandoko	541 1.4×	319 1.4×	21 0.3×	46 0.6×	28 0.4×	13	672

Countries citing papers authored by Etrusca D’Urbano

Since Specialization

Citations

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

Fields of papers citing papers by Etrusca D’Urbano

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Etrusca D’Urbano. 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 Etrusca D’Urbano. The network helps show where Etrusca D’Urbano may publish in the future.

Co-authorship network of co-authors of Etrusca D’Urbano

This figure shows the co-authorship network connecting the top 25 collaborators of Etrusca D’Urbano. A scholar is included among the top collaborators of Etrusca D’Urbano 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 Etrusca D’Urbano. Etrusca D’Urbano 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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