Ivan Cuccovillo
Impact in
- Immunology top 5%
- Biomarkers in Disease Mechanisms
- Genetics top 5%
- Virus-based gene therapy research
- Myeloproliferative Neoplasms: Diagnosis and Treatment
Papers in
- Immunology 16
- Biomarkers in Disease Mechanisms 16
- Genetics 3
- Virus-based gene therapy research 5
- Co-authors
- Alberto MantovaniFabio FiordalisoRoberto LatiniMirko DoniLidia StaszewskyBarbara BottazziAnna Kajaste‐RudnitskiMonica Salio
- Journals
- Life Sciences (2 papers)Human Gene Therapy (1 paper)Molecular Therapy (1 paper)Journal of Molecular and Cellular Cardiology (1 paper)Journal of Nephrology (1 paper)
- Partner nations
- ItalyUnited KingdomUnited States
In The Last Decade
Ivan Cuccovillo
28 papers receiving 1.6k citations
Peers
Comparison fields: 5 of 103
- Immunology 496
- Genetics 237
- Hematology 242
- Cardiology and Cardiovascular Medicine 269
- Nephrology 65
Countries citing papers authored by Ivan Cuccovillo
This map shows the geographic impact of Ivan Cuccovillo'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 Ivan Cuccovillo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ivan Cuccovillo more than expected).
Fields of papers citing papers by Ivan Cuccovillo
This network shows the impact of papers produced by Ivan Cuccovillo. 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 Ivan Cuccovillo. The network helps show where Ivan Cuccovillo may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Ivan Cuccovillo, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 2 | |
| 2 | 2023 | 6 | |
| 3 | 2020 | 163 | |
| 4 | 2020 | 25 | |
| 5 | 2019 | 8 | |
| 6 | 2018 | 79 | |
| 7 | 2017 | 55 | |
| 8 | 2013 | 2 | |
| 9 | 2012 | 80 | |
| 10 | 2012 | 16 | |
| 11 | 2012 | 60 | |
| 12 | 2011 | 79 | |
| 13 | 2011 | 17 | |
| 14 | 2011 | 7 | |
| 15 | 2010 | 28 | |
| 16 | 2010 | 122 | |
| 17 | 2008 | 79 | |
| 18 | 2007 | 22 | |
| 19 | 2006 | 97 | |
| 20 | 2004 | 170 |
About Ivan Cuccovillo
Ivan Cuccovillo is a scholar working on Immunology, Genetics, Genetics, Cardiology and Cardiovascular Medicine and Molecular Biology, having authored 29 papers that have together received 1.6k indexed citations. Recurring topics across this work include Biomarkers in Disease Mechanisms (16 papers), Virus-based gene therapy research (5 papers), RNA Interference and Gene Delivery (3 papers), CRISPR and Genetic Engineering (3 papers), CAR-T cell therapy research (2 papers), Tissue Engineering and Regenerative Medicine (2 papers), Congenital heart defects research (2 papers) and Inflammasome and immune disorders (2 papers). The work is most often cited by research in Immunology (496 citations), Genetics (237 citations), Hematology (242 citations), Cardiology and Cardiovascular Medicine (269 citations) and Nephrology (65 citations). Ivan Cuccovillo has collaborated with scholars based in Italy, United Kingdom and United States. Frequent co-authors include Alberto Mantovani, Fabio Fiordaliso, Roberto Latini, Mirko Doni, Lidia Staszewsky, Barbara Bottazzi, Anna Kajaste‐Rudnitski, Monica Salio, Antonio Bai and Pietro Ghezzi. Their work appears in journals such as Life Sciences, Human Gene Therapy, Molecular Therapy, Journal of Molecular and Cellular Cardiology and Journal of Nephrology.
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.