Fabio Petrocca
- Molecular Biology top 0.5%
- Cancer Research top 0.05%
- Oncology top 1%
- Immunology top 5%
- Hematology top 2%
- Co-authors
- Carlo M. CroceStefano VoliniaRosa VisoneAndrea VecchioneGeorge A. CalinChang‐Gong LiuMarilena V. IorioMassimo Negrini
- Topics
- MicroRNA in disease regulation (15 papers)CAR-T cell therapy research (13 papers)Cancer-related molecular mechanisms research (11 papers)
- Partner nations
- United StatesItalySpain
In The Last Decade
Fabio Petrocca
39 papers receiving 10.8k citations
Hit Papers
Peers
Comparison fields: 5 of 130
- Molecular Biology 9.2k
- Cancer Research 8.3k
- Oncology 1.7k
- Immunology 620
- Hematology 414
Countries citing papers authored by Fabio Petrocca
This map shows the geographic impact of Fabio Petrocca'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 Fabio Petrocca with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fabio Petrocca more than expected).
Fields of papers citing papers by Fabio Petrocca
This network shows the impact of papers produced by Fabio Petrocca. 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 Fabio Petrocca. The network helps show where Fabio Petrocca may publish in the future.
Co-authorship network of co-authors of Fabio Petrocca
This figure shows the co-authorship network connecting the top 25 collaborators of Fabio Petrocca. A scholar is included among the top collaborators of Fabio Petrocca based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Fabio Petrocca. Fabio Petrocca is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 66 | |
| 3 | 4 | |
| 4 | 66 | |
| 5 | 36 | |
| 6 | 69 | |
| 7 | 101 | |
| 8 | 141 | |
| 9 | 28 | |
| 10 | 13 | |
| 11 | 260 | |
| 12 | 42 | |
| 13 | Genomic Profiling of MicroRNA and Messenger RNA Reveals Deregulated MicroRNA Expression in Prostate Cancerbreakdown → | 591 |
| 14 | 43 | |
| 15 | MicroRNA Signatures in Human Ovarian Cancerbreakdown → | 1199 |
| 16 | 312 | |
| 17 | MicroRNA Expression Patterns to Differentiate Pancreatic Adenocarcinoma From Normal Pancreas and Chronic Pancreatitisbreakdown → | 939 |
| 18 | 361 | |
| 19 | A microRNA expression signature of human solid tumors defines cancer gene targetsbreakdown → | 4730 |
| 20 | 37 |
About Fabio Petrocca
Fabio Petrocca is a scholar working on Cancer Research, Hematology and Oncology, having authored 39 papers that have together received 11.0k indexed citations. Recurring topics across this work include MicroRNA in disease regulation (15 papers), CAR-T cell therapy research (13 papers) and Cancer-related molecular mechanisms research (11 papers). The work is most often cited by research in Cancer Research (8.3k citations), Molecular Biology (9.2k citations) and Oncology (1.7k citations). Fabio Petrocca has collaborated with scholars based in United States, Italy and Spain. Frequent co-authors include Carlo M. Croce, Stefano Volinia, Rosa Visone, Andrea Vecchione, George A. Calin, Chang‐Gong Liu, Marilena V. Iorio, Massimo Negrini, Stefan Ambs and Robyn L. Prueitt. Their work appears in journals such as Proceedings of the National Academy of Sciences, JAMA and Nature Communications.
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.