Antonio Di Stasi
- Oncology top 1%
- CAR-T cell therapy research 18
- Immunology top 2%
- Hematology top 2%
- Hematopoietic Stem Cell Transplantation 13
- Acute Myeloid Leukemia Research 12
- Chronic Myeloid Leukemia Treatments 8
- Genetics top 2%
- Virus-based gene therapy research 11
- Biomedical Engineering top 5%
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- Acute Lymphoblastic Leukemia research 6
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- CRISPR and Genetic Engineering 5
- Viral Infectious Diseases and Gene Expression in Insects 3
- Co-authors
- Malcolm K. BrennerBarbara SavoldoGianpietro DottiHelen E. HeslopCliona M. RooneyDavid M. SpencerAdrian P. GeeCaridad Martinez
- Cited by
- OncologyImmunologyHematology
- Journals
- Blood (9 papers)Biology of Blood and Marrow Transplantation (5 papers)Bone Marrow Transplantation (3 papers)
- Partner nations
- United StatesItalySouth Africa
In The Last Decade
Antonio Di Stasi
41 papers receiving 2.7k citations
Hit Papers
Peers
Comparison fields: 5 of 69
- Oncology 2.2k
- Immunology 954
- Hematology 374
- Genetics 916
- Biomedical Engineering 648
Countries citing papers authored by Antonio Di Stasi
This map shows the geographic impact of Antonio Di Stasi'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 Antonio Di Stasi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Antonio Di Stasi more than expected).
Fields of papers citing papers by Antonio Di Stasi
This network shows the impact of papers produced by Antonio Di Stasi. 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 Antonio Di Stasi. The network helps show where Antonio Di Stasi may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Antonio Di Stasi, 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 | 0 | |
| 3 | 2022 | 10 | |
| 4 | 2022 | 2 | |
| 5 | 2022 | 8 | |
| 6 | 2019 | 4 | |
| 7 | 2018 | 3 | |
| 8 | 2018 | 35 | |
| 9 | 2018 | 10 | |
| 10 | 2016 | 70 | |
| 11 | 2015 | 83 | |
| 12 | 2015 | 21 | |
| 13 | 2014 | 25 | |
| 14 | 2014 | 179 | |
| 15 | 2014 | 7 | |
| 16 | 2014 | 2 | |
| 17 | 2014 | 35 | |
| 18 | Inducible Apoptosis as a Safety Switch for Adoptive Cell Therapybreakdown → | 2011 | 1159 |
| 19 | 2010 | 5 | |
| 20 | 2010 | 24 |
About Antonio Di Stasi
Antonio Di Stasi is a scholar working on Hematology, Oncology, Genetics, Transplantation and Immunology, having authored 42 papers that have together received 2.8k indexed citations. Recurring topics across this work include CAR-T cell therapy research (18 papers), Hematopoietic Stem Cell Transplantation (13 papers), Acute Myeloid Leukemia Research (12 papers), Virus-based gene therapy research (11 papers), Chronic Myeloid Leukemia Treatments (8 papers), Acute Lymphoblastic Leukemia research (6 papers), CRISPR and Genetic Engineering (5 papers) and Viral Infectious Diseases and Gene Expression in Insects (3 papers). The work is most often cited by research in Oncology (2.2k citations), Immunology (954 citations), Hematology (374 citations), Genetics (916 citations) and Biomedical Engineering (648 citations). Antonio Di Stasi has collaborated with scholars based in United States, Italy and South Africa. Frequent co-authors include Malcolm K. Brenner, Barbara Savoldo, Gianpietro Dotti, Helen E. Heslop, Cliona M. Rooney, David M. Spencer, Adrian P. Gee, Caridad Martinez, Bambi Grilley and Hao Liu. Their work appears in journals such as Blood, Biology of Blood and Marrow Transplantation, Bone Marrow Transplantation, Frontiers in Immunology and Stem Cells.
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.