Massimo Geuna
- Genetics top 0.5%
- Chronic Lymphocytic Leukemia Research 16
- Virus-based gene therapy research 5
- Immunology top 2%
- Immune Cell Function and Interaction 13
- T-cell and B-cell Immunology 10
- Immunotherapy and Immune Responses 6
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- Lymphoma Diagnosis and Treatment 18
- Oncology top 2%
- Physiology top 2%
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- Cancer Genomics and Diagnostics 7
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- Monoclonal and Polyclonal Antibodies Research 7
- Co-authors
- Luigi NaldiniLaurie AillesAntonia FollenziFederico Caligaris‐CappioPaolo GhiaCristina ScielzoGiuseppe GuidaStefania Stella
- Journals
- Blood (7 papers)European Journal of Immunology (3 papers)European Journal Of Haematology (3 papers)
- Partner nations
- ItalyUnited StatesUnited Kingdom
In The Last Decade
Massimo Geuna
84 papers receiving 4.3k citations
Hit Papers
Peers
Comparison fields: 5 of 111
- Genetics 1.1k
- Immunology 1.5k
- Pathology and Forensic Medicine 983
- Oncology 1.1k
- Physiology 161
Countries citing papers authored by Massimo Geuna
This map shows the geographic impact of Massimo Geuna'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 Massimo Geuna with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Massimo Geuna more than expected).
Fields of papers citing papers by Massimo Geuna
This network shows the impact of papers produced by Massimo Geuna. 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 Massimo Geuna. The network helps show where Massimo Geuna may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Massimo Geuna, 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 | 1 | |
| 2 | 2022 | 10 | |
| 3 | 2020 | 25 | |
| 4 | 2018 | 12 | |
| 5 | 2012 | 29 | |
| 6 | 2011 | 5 | |
| 7 | 2010 | 288 | |
| 8 | 2001 | 116 | |
| 9 | 2001 | 91 | |
| 10 | 2000 | 22 | |
| 11 | 1997 | 52 | |
| 12 | 1996 | 15 | |
| 13 | 1996 | 40 | |
| 14 | p53 overexpression, DNA ploidy and cell proliferative activity are prognostic factors in stage I-II thymomas | 1995 | 1 |
| 15 | 1995 | 50 | |
| 16 | 1995 | 2 | |
| 17 | 1993 | 6 | |
| 18 | 1992 | 151 | |
| 19 | 1990 | 108 | |
| 20 | 1989 | 22 |
About Massimo Geuna
Massimo Geuna is a scholar working on Genetics, Physiology, Immunology, Pathology and Forensic Medicine and Immunology and Allergy, having authored 84 papers that have together received 4.4k indexed citations. Recurring topics across this work include Lymphoma Diagnosis and Treatment (18 papers), Chronic Lymphocytic Leukemia Research (16 papers), Immune Cell Function and Interaction (13 papers), T-cell and B-cell Immunology (10 papers), Cancer Genomics and Diagnostics (7 papers), Monoclonal and Polyclonal Antibodies Research (7 papers), Immunotherapy and Immune Responses (6 papers) and Virus-based gene therapy research (5 papers). The work is most often cited by research in Genetics (1.1k citations), Immunology (1.5k citations), Pathology and Forensic Medicine (983 citations), Oncology (1.1k citations) and Physiology (161 citations). Massimo Geuna has collaborated with scholars based in Italy, United States and United Kingdom. Frequent co-authors include Luigi Naldini, Laurie Ailles, Antonia Follenzi, Federico Caligaris‐Cappio, Paolo Ghia, Cristina Scielzo, Giuseppe Guida, Stefania Stella, Giuliana Strola and Luisa Granziero. Their work appears in journals such as Blood, European Journal of Immunology, European Journal Of Haematology, Human Gene Therapy and Journal of Cellular Physiology.
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.