Chiara Parravicini

73 total papers · 1.8k total citations
40 papers, 1.4k citations indexed

About

Chiara Parravicini is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Oncology. According to data from OpenAlex, Chiara Parravicini has authored 40 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Molecular Biology, 14 papers in Cellular and Molecular Neuroscience and 9 papers in Oncology. Recurrent topics in Chiara Parravicini's work include Receptor Mechanisms and Signaling (11 papers), Neuropeptides and Animal Physiology (9 papers) and Chemical Synthesis and Analysis (4 papers). Chiara Parravicini is often cited by papers focused on Receptor Mechanisms and Signaling (11 papers), Neuropeptides and Animal Physiology (9 papers) and Chemical Synthesis and Analysis (4 papers). Chiara Parravicini collaborates with scholars based in Italy, Austria and Germany. Chiara Parravicini's co-authors include Ivano Eberini, Maria P. Abbracchio, Maria Letizia Trincavelli, Davide Lecca, Claudia Martini, Marta Fumagalli, Luca Palazzolo, Patrizia Rosa, Claudia Verderio and Simona Daniele and has published in prestigious journals such as Journal of Biological Chemistry, The EMBO Journal and PLoS ONE.

In The Last Decade

Chiara Parravicini

40 papers receiving 1.4k citations

Author Peers

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

Author Last Decade Papers Cites
Chiara Parravicini 819 266 184 181 170 40 1.4k
Jacinth Naidoo 785 1.0× 234 0.9× 212 1.2× 172 1.0× 157 0.9× 22 1.7k
Terry Joe Sprinkle 753 0.9× 343 1.3× 138 0.8× 424 2.3× 129 0.8× 44 1.6k
Sang Yoon Lee 776 0.9× 184 0.7× 173 0.9× 37 0.2× 103 0.6× 44 1.5k
Yuiko Tsukada 579 0.7× 309 1.2× 251 1.4× 138 0.8× 100 0.6× 53 1.3k
San‐Hua Fang 858 1.0× 343 1.3× 310 1.7× 307 1.7× 110 0.6× 56 1.8k
Tapas K. Makar 450 0.5× 329 1.2× 237 1.3× 236 1.3× 66 0.4× 38 1.2k
María Delgado‐Esteban 773 0.9× 227 0.9× 303 1.6× 99 0.5× 130 0.8× 27 1.4k
Yukiko Kaneko 648 0.8× 141 0.5× 181 1.0× 213 1.2× 208 1.2× 48 1.6k
Yuri Ikeda‐Matsuo 428 0.5× 274 1.0× 284 1.5× 97 0.5× 61 0.4× 43 1.4k
Zoran Redzic 308 0.4× 382 1.4× 159 0.9× 99 0.5× 175 1.0× 45 1.3k

Countries citing papers authored by Chiara Parravicini

Since Specialization
Citations

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

Fields of papers citing papers by Chiara Parravicini

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chiara Parravicini

This figure shows the co-authorship network connecting the top 25 collaborators of Chiara Parravicini. A scholar is included among the top collaborators of Chiara Parravicini 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 Chiara Parravicini. Chiara Parravicini 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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2026