Danilo Perrotti
- Hematology top 0.2%
- Chronic Myeloid Leukemia Treatments 54
- Acute Myeloid Leukemia Research 43
- Multiple Myeloma Research and Treatments 11
- Genetics top 0.5%
- Chronic Lymphocytic Leukemia Research 21
- Myeloproliferative Neoplasms: Diagnosis and Treatment 13
- Cancer Research top 0.5%
- MicroRNA in disease regulation 11
- Molecular Biology top 1%
- Protein Degradation and Inhibitors 11
- RNA Interference and Gene Delivery 10
- Immunology top 2%
- Co-authors
- Bruno CalabrettaPaolo NevianiMichael A. CaligiuriGuido MarcucciRamasamy SanthanamRossana TrottaTomasz SkórskiCarlo M. Croce
- Cited by
- HematologyGeneticsCancer Research
- Journals
- Blood (44 papers)Proceedings of the National Academy of Sciences (8 papers)Cancer Research (6 papers)
- Partner nations
- United StatesItalyCanada
In The Last Decade
Danilo Perrotti
121 papers receiving 8.8k citations
Hit Papers
Peers
Comparison fields: 5 of 118
- Hematology 3.2k
- Genetics 1.7k
- Cancer Research 2.1k
- Molecular Biology 5.9k
- Immunology 1.3k
Countries citing papers authored by Danilo Perrotti
This map shows the geographic impact of Danilo Perrotti'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 Danilo Perrotti with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Danilo Perrotti more than expected).
Fields of papers citing papers by Danilo Perrotti
This network shows the impact of papers produced by Danilo Perrotti. 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 Danilo Perrotti. The network helps show where Danilo Perrotti may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Danilo Perrotti, 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 | 2021 | 17 | |
| 2 | 2021 | 5 | |
| 3 | 2017 | 36 | |
| 4 | 2016 | 19 | |
| 5 | 2015 | 54 | |
| 6 | 2014 | 84 | |
| 7 | 2013 | 151 | |
| 8 | 2013 | 320 | |
| 9 | MicroRNAs bind to Toll-like receptors to induce prometastatic inflammatory responsebreakdown → | 2012 | 1284 |
| 10 | 2010 | 100 | |
| 11 | 2010 | 289 | |
| 12 | 2009 | 235 | |
| 13 | 2009 | 20 | |
| 14 | 2008 | 39 | |
| 15 | 2008 | 207 | |
| 16 | 2007 | 269 | |
| 17 | 2005 | 370 | |
| 18 | 2003 | 180 | |
| 19 | 2002 | 100 | |
| 20 | 1998 | 113 |
About Danilo Perrotti
Danilo Perrotti is a scholar working on Hematology, Genetics and Cancer Research, having authored 123 papers that have together received 9.0k indexed citations. Recurring topics across this work include Chronic Myeloid Leukemia Treatments (54 papers), Acute Myeloid Leukemia Research (43 papers), Chronic Lymphocytic Leukemia Research (21 papers), Myeloproliferative Neoplasms: Diagnosis and Treatment (13 papers), Multiple Myeloma Research and Treatments (11 papers), MicroRNA in disease regulation (11 papers), Protein Degradation and Inhibitors (11 papers) and RNA Interference and Gene Delivery (10 papers). The work is most often cited by research in Hematology (3.2k citations), Genetics (1.7k citations) and Cancer Research (2.1k citations). Danilo Perrotti has collaborated with scholars based in United States, Italy and Canada. Frequent co-authors include Bruno Calabretta, Paolo Neviani, Michael A. Caligiuri, Guido Marcucci, Ramasamy Santhanam, Rossana Trotta, Tomasz Skórski, Carlo M. Croce, Clara D. Bloomfield and John M. Goldman. Their work appears in journals such as Blood, Proceedings of the National Academy of Sciences, Cancer Research, Cancer Cell and Journal of Clinical Oncology.
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.