Claudio D’Amore

72 papers receiving 2.4k citations

Claudio D’Amore's Hit Papers

Protein kinase CK2: a potential therapeutic target for diverse human diseases 2021 · 223 citations
2230+1+3Years since publication50100150200

Peers

Claudio D’Amore
Comparison fields: 5 of 108
  • Oncology 854
  • Hepatology 227
  • Toxicology 93
  • Biotechnology 209
  • Pharmacology 189
Replace Xian‐Hui He with:
Xian‐Hui He China
Kazuhiro Katayama Japan
M. Tien Kuo United States
John W. Gillard Canada
George G. Chen Hong Kong
Béatrice Bailly‐Maitre France
Joell J. Gills United States
Maria Thomas Germany
Martin G. Belinsky United States
Mitchell Hull United States
Claudio D’Amore relative to Xian‐Hui He China Xian‐Hui He's profile →
Citations per field
00.5×4.0×
Xian‐Hui He · 1×
Citations per year

Countries citing papers authored by Claudio D’Amore

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

Border = papers with Claudio D’Amore Line = papers co-authored together Claudio D’Amore links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

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 →
2021223
2 2013124
3 2011100
4 201397
5 201294
6 201182
7 201480
8 201271
9 201471
10 201163
11 202063
12 201463
13 201162
14 201162
15 201252
16 201549
17 201349
18 201249
19 201147
20 201347

About Claudio D’Amore

Claudio D’Amore is a scholar working on Molecular Biology, Oncology, Surgery, Epidemiology 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 (18 papers), Estrogen and related hormone effects (10 papers), Cholesterol and Lipid Metabolism (10 papers), Liver Disease Diagnosis and Treatment (6 papers), HIV-related health complications and treatments (5 papers), Cystic Fibrosis Research Advances (5 papers), HIV Research and Treatment (5 papers) and Marine Sponges and Natural Products (5 papers). The work is most often cited by research in Oncology (854 citations), Hepatology (227 citations), Toxicology (93 citations), Biotechnology (209 citations) and Pharmacology (189 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, Eleonora Distrutti, Mauro Salvi, Christian Borgo, Valentina Sepe and Stefania Sarno. 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.

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