Stefano Costanzi

6.4k citations
148 papers · 4.5k indexed · h-index 39

Stefano Costanzi

142 papers receiving 4.4k citations

Peers

Stefano Costanzi
Comparison fields: 5 of 134
  • Physiology 1.2k
  • Cellular and Molecular Neuroscience 1.0k
  • Computational Theory and Mathematics 642
  • Molecular Biology 2.7k
  • Organic Chemistry 561
Replace Kazuhiro Hasegawa with:
Kazuhiro Hasegawa Japan
Clemens Steegborn Germany
Michael V. Milburn United States
Taku Nagao Japan
Sharron H. Francis United States
Dolores Pérez‐Sala Spain
Paul A. Hyslop United States
Yong‐Yeon Cho South Korea
John M. Lowenstein United States
Yasuo Ohno Japan
Stefano Costanzi relative to Kazuhiro Hasegawa Japan Kazuhiro Hasegawa's profile →
Citations per field
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Kazuhiro Hasegawa · 1×
Citations per year

Countries citing papers authored by Stefano Costanzi

Since Specialization
Citations

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

Fields of papers citing papers by Stefano Costanzi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Stefano Costanzi, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Stefano Costanzi Line = papers co-authored together Stefano Costanzi links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 20236
3 20191
4
Characterization of GPR101 transcripts structure, expression and signaling
20160
5 201615
6 20150
7 201513
8 20137
9 201219
10 201128
11 20119
12 201137
13 200880
14 200644
15 200630
16 200546
17 200511
18 20032
19 2001278
20 20013

About Stefano Costanzi

Stefano Costanzi is a scholar working on Physiology, Cellular and Molecular Neuroscience and Computational Theory and Mathematics, having authored 148 papers that have together received 4.5k indexed citations. Recurring topics across this work include Receptor Mechanisms and Signaling (71 papers), Adenosine and Purinergic Signaling (50 papers), Neuropeptides and Animal Physiology (34 papers), Computational Drug Discovery Methods (26 papers), Pharmacological Receptor Mechanisms and Effects (19 papers), Biochemical and Molecular Research (12 papers), Monoclonal and Polyclonal Antibodies Research (12 papers) and Calcium signaling and nucleotide metabolism (8 papers). The work is most often cited by research in Physiology (1.2k citations), Cellular and Molecular Neuroscience (1.0k citations) and Computational Theory and Mathematics (642 citations). Stefano Costanzi has collaborated with scholars based in United States, Italy and Germany. Frequent co-authors include Kenneth A. Jacobson, Santiago Vilar, Rosaria Volpini, Sauro Vittori, Gloria Cristalli, Marvin C. Gershengorn, Irina G. Tikhonova, Susanne Neumann, Catia Lambertucci and Bruce M. Raaka. Their work appears in journals such as Journal of the American Chemical Society, Journal of Biological Chemistry and PLoS ONE.

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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