Claudio D’Amore
Impact in
- Oncology top 5%
- Drug Transport and Resistance Mechanisms
- Toxicology top 2%
Papers in
-
- Protein Kinase Regulation and GTPase Signaling 6
- Oncology 18
- Drug Transport and Resistance Mechanisms 15
- Co-authors
- Stefano Fiorucci (49 shared papers)Barbara Renga (44 shared papers)Andrea Mencarelli (24 shared papers)Sabrina Cipriani (24 shared papers)Angela Zampella (26 shared papers)Mauro Salvi (16 shared papers)Christian Borgo (14 shared papers)Eleonora Distrutti (16 shared papers)
- Journals
- Journal of Medicinal Chemistry (10 papers)PLoS ONE (8 papers)Marine Drugs (6 papers)International Journal of Molecular Sciences (4 papers)Steroids (3 papers)
- Partner nations
- ItalyJapanNew Zealand
In The Last Decade
Claudio D’Amore
72 papers receiving 2.4k citations
Claudio D’Amore's Hit Papers
Peers
Comparison fields: 5 of 107
- Oncology 812
- Toxicology 93
- Hepatology 189
- Biotechnology 207
- Pharmacology 186
Countries citing papers authored by Claudio D’Amore
This map shows the geographic impact of Claudio D’Amore'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 Claudio D’Amore with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Claudio D’Amore more than expected).
Fields of papers citing papers by Claudio D’Amore
This network shows the impact of papers produced by Claudio D’Amore. 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 Claudio D’Amore. The network helps show where Claudio D’Amore may publish in the future.
Co-authors
The 25 scholars most cited alongside Claudio D’Amore, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 72 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Protein kinase CK2: a potential therapeutic target for diverse human diseases Hit paper breakdown → | 2021 | 233 |
| 2 | 2013 | 128 | |
| 3 | 2011 | 101 | |
| 4 | 2013 | 95 | |
| 5 | 2012 | 94 | |
| 6 | 2011 | 83 | |
| 7 | 2014 | 82 | |
| 8 | 2014 | 72 | |
| 9 | 2012 | 71 | |
| 10 | 2014 | 65 | |
| 11 | 2020 | 64 | |
| 12 | 2011 | 63 | |
| 13 | 2011 | 62 | |
| 14 | 2011 | 62 | |
| 15 | 2012 | 53 | |
| 16 | 2012 | 51 | |
| 17 | 2013 | 50 | |
| 18 | 2015 | 49 | |
| 19 | 2011 | 48 | |
| 20 | 2013 | 47 |
About Claudio D’Amore
Claudio D’Amore is a scholar working on Molecular Biology, Oncology, Surgery, Genetics and Immunology, having authored 72 papers that have together received 2.4k indexed citations. Recurring topics across this work include Drug Transport and Resistance Mechanisms (15 papers), Cholesterol and Lipid Metabolism (10 papers), Estrogen and related hormone effects (10 papers), Protein Kinase Regulation and GTPase Signaling (6 papers), Hormonal Regulation and Hypertension (5 papers), Marine Sponges and Natural Products (5 papers), Cystic Fibrosis Research Advances (5 papers) and Pharmacogenetics and Drug Metabolism (4 papers). The work is most often cited by research in Oncology (812 citations), Toxicology (93 citations), Hepatology (189 citations), Biotechnology (207 citations) and Pharmacology (186 citations). Claudio D’Amore has collaborated with scholars based in Italy, Japan and New Zealand. Frequent co-authors include Stefano Fiorucci, Barbara Renga, Andrea Mencarelli, Sabrina Cipriani, Angela Zampella, Mauro Salvi, Christian Borgo, Eleonora Distrutti, Stefania Sarno and Valentina Sepe. Their work appears in journals such as Journal of Medicinal Chemistry, PLoS ONE, Marine Drugs, International Journal of Molecular Sciences and Steroids.
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.