Anne Banos
Impact in
- Hematology top 5%
- Acute Myeloid Leukemia Research
- Multiple Myeloma Research and Treatments
- Genetics top 10%
- Chronic Lymphocytic Leukemia Research
Papers in
- Hematology 19
- Acute Myeloid Leukemia Research 9
- Multiple Myeloma Research and Treatments 8
- Chronic Myeloid Leukemia Treatments 4
- Genetics 14
- Chronic Lymphocytic Leukemia Research 13
- Co-authors
- Pierre Fenaux (8 shared papers)Michel Blanc (4 shared papers)Norbert Vey (7 shared papers)Caroline Besson (4 shared papers)Katja Weisel (6 shared papers)Guillaume Cartron (3 shared papers)Jesús F. San Miguel (6 shared papers)Martha Q. Lacy (5 shared papers)
- Journals
- Blood (15 papers)Journal of Clinical Oncology (5 papers)British Journal of Haematology (2 papers)Annals of Hematology (1 paper)Leukemia Research (1 paper)
- Partner nations
- FranceGreeceUnited States
In The Last Decade
Anne Banos
25 papers receiving 253 citations
Peers
Comparison fields: 5 of 37
- Hematology 167
- Genetics 81
- Pathology and Forensic Medicine 57
- Oncology 73
- Molecular Biology 127
Countries citing papers authored by Anne Banos
This map shows the geographic impact of Anne Banos'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 Anne Banos with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Anne Banos more than expected).
Fields of papers citing papers by Anne Banos
This network shows the impact of papers produced by Anne Banos. 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 Anne Banos. The network helps show where Anne Banos may publish in the future.
Co-authors
The 25 scholars most cited alongside Anne Banos, 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 27 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2014 | 36 | |
| 2 | 2011 | 29 | |
| 3 | 2011 | 28 | |
| 4 | 2012 | 28 | |
| 5 | 2017 | 21 | |
| 6 | 2014 | 17 | |
| 7 | 2013 | 13 | |
| 8 | 2013 | 12 | |
| 9 | 2013 | 10 | |
| 10 | 2019 | 10 | |
| 11 | 2019 | 7 | |
| 12 | 2009 | 7 | |
| 13 | 2017 | 7 | |
| 14 | 2020 | 6 | |
| 15 | 2013 | 6 | |
| 16 | 2013 | 5 | |
| 17 | 2010 | 5 | |
| 18 | 2014 | 3 | |
| 19 | 2024 | 2 | |
| 20 | 2013 | 2 |
About Anne Banos
Anne Banos is a scholar working on Hematology, Genetics, Pathology and Forensic Medicine, Molecular Biology and Oncology, having authored 27 papers that have together received 261 indexed citations. Recurring topics across this work include Chronic Lymphocytic Leukemia Research (13 papers), Lymphoma Diagnosis and Treatment (11 papers), Acute Myeloid Leukemia Research (9 papers), Multiple Myeloma Research and Treatments (8 papers), Protein Degradation and Inhibitors (6 papers), Acute Lymphoblastic Leukemia research (6 papers), Chronic Myeloid Leukemia Treatments (4 papers) and Cancer Treatment and Pharmacology (4 papers). The work is most often cited by research in Hematology (167 citations), Genetics (81 citations), Pathology and Forensic Medicine (57 citations), Oncology (73 citations) and Molecular Biology (127 citations). Anne Banos has collaborated with scholars based in France, Greece and United States. Frequent co-authors include Pierre Fenaux, Michel Blanc, Norbert Vey, Caroline Besson, Katja Weisel, Guillaume Cartron, Jesús F. San Miguel, Martha Q. Lacy, François Dreyfus and Kevin Song. Their work appears in journals such as Blood, Journal of Clinical Oncology, British Journal of Haematology, Annals of Hematology and Leukemia Research.
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.