Giulia Cheloni
Impact in
- Hematology top 5%
- Chronic Myeloid Leukemia Treatments
- Acute Myeloid Leukemia Research
- Cancer Research top 10%
- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
- Cancer, Hypoxia, and Metabolism
Papers in
- Hematology 14
- Chronic Myeloid Leukemia Treatments 10
- Acute Myeloid Leukemia Research 6
- Hematopoietic Stem Cell Transplantation 3
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- PI3K/AKT/mTOR signaling in cancer 5
- Protein Degradation and Inhibitors 3
- Co-authors
- Persio Dello Sbarba (10 shared papers)Elisabetta Rovida (9 shared papers)Shaoguang Li (4 shared papers)Ignazia Tusa (7 shared papers)Antonella Gozzini (6 shared papers)Yi Shan (3 shared papers)Michele Tanturli (3 shared papers)Cong Peng (2 shared papers)
- Journals
- Blood (5 papers)Cell Research (2 papers)Cell Cycle (2 papers)Nature Methods (1 paper)Cancer Discovery (1 paper)
- Partner nations
- United StatesItalyFrance
In The Last Decade
Giulia Cheloni
20 papers receiving 476 citations
Peers
Comparison fields: 5 of 58
- Hematology 184
- Cancer Research 173
- Genetics 85
- Molecular Biology 316
- Oncology 63
Countries citing papers authored by Giulia Cheloni
This map shows the geographic impact of Giulia Cheloni'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 Giulia Cheloni with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Giulia Cheloni more than expected).
Fields of papers citing papers by Giulia Cheloni
This network shows the impact of papers produced by Giulia Cheloni. 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 Giulia Cheloni. The network helps show where Giulia Cheloni may publish in the future.
Co-authors
The 25 scholars most cited alongside Giulia Cheloni, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 128 | |
| 2 | 2016 | 73 | |
| 3 | 2017 | 69 | |
| 4 | 2014 | 51 | |
| 5 | 2014 | 41 | |
| 6 | 2013 | 24 | |
| 7 | 2018 | 20 | |
| 8 | 2017 | 17 | |
| 9 | 2022 | 11 | |
| 10 | 2015 | 11 | |
| 11 | 2020 | 8 | |
| 12 | 2021 | 7 | |
| 13 | 2021 | 6 | |
| 14 | 2016 | 6 | |
| 15 | 2019 | 3 | |
| 16 | 2021 | 3 | |
| 17 | 2020 | 2 | |
| 18 | 2017 | 1 | |
| 19 | 2021 | 1 | |
| 20 | 2021 | 1 |
About Giulia Cheloni
Giulia Cheloni is a scholar working on Hematology, Molecular Biology, Oncology, Genetics and Immunology, having authored 22 papers that have together received 483 indexed citations. Recurring topics across this work include Chronic Myeloid Leukemia Treatments (10 papers), Acute Myeloid Leukemia Research (6 papers), PI3K/AKT/mTOR signaling in cancer (5 papers), Chronic Lymphocytic Leukemia Research (4 papers), CAR-T cell therapy research (4 papers), Immunotherapy and Immune Responses (4 papers), Protein Degradation and Inhibitors (3 papers) and Hematopoietic Stem Cell Transplantation (3 papers). The work is most often cited by research in Hematology (184 citations), Cancer Research (173 citations), Genetics (85 citations), Molecular Biology (316 citations) and Oncology (63 citations). Giulia Cheloni has collaborated with scholars based in United States, Italy and France. Frequent co-authors include Persio Dello Sbarba, Elisabetta Rovida, Shaoguang Li, Ignazia Tusa, Antonella Gozzini, Yi Shan, Michele Tanturli, Cong Peng, Ilaria Marzi and Mark Simpson. Their work appears in journals such as Blood, Cell Research, Cell Cycle, Nature Methods and Cancer Discovery.
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.