Michael R. Savona
- Hematology top 0.2%
- Acute Myeloid Leukemia Research 100
- Chronic Myeloid Leukemia Treatments 43
- Multiple Myeloma Research and Treatments 21
- Genetics top 0.5%
- Myeloproliferative Neoplasms: Diagnosis and Treatment 43
- Chronic Lymphocytic Leukemia Research 39
- Virology top 2%
- Molecular Biology top 5%
- Protein Degradation and Inhibitors 19
- Histone Deacetylase Inhibitors Research 16
- Oncology top 5%
-
- Acute Lymphoblastic Leukemia research 24
- Co-authors
- Moshe TalpazStephen A. StricklandAdewunmi Onafuwa-NugaLucy A. McNamaraKathleen L. CollinsJames RiddellDale L. BixbyGail J. Roboz
- Cited by
- HematologyGeneticsVirology
- Journals
- Proceedings of the National Academy of Sciences (1 paper)JAMA (1 paper)Nucleic Acids Research (1 paper)
- Partner nations
- United StatesCanadaItaly
In The Last Decade
Michael R. Savona
200 papers receiving 4.3k citations
Hit Papers
Peers
Comparison fields: 5 of 125
- Hematology 2.4k
- Genetics 1.1k
- Virology 271
- Molecular Biology 2.2k
- Oncology 773
Countries citing papers authored by Michael R. Savona
This map shows the geographic impact of Michael R. Savona'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 Michael R. Savona with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael R. Savona more than expected).
Fields of papers citing papers by Michael R. Savona
This network shows the impact of papers produced by Michael R. Savona. 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 Michael R. Savona. The network helps show where Michael R. Savona may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Michael R. Savona, 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 | 2025 | 0 | |
| 2 | 2024 | 16 | |
| 3 | 2024 | 6 | |
| 4 | 2024 | 4 | |
| 5 | 2024 | 19 | |
| 6 | 2023 | 1 | |
| 7 | 2023 | 74 | |
| 8 | 2022 | 3 | |
| 9 | 2022 | 10 | |
| 10 | 2022 | 3 | |
| 11 | 2021 | 2 | |
| 12 | 2020 | 15 | |
| 13 | Venetoclax Combined With Low-Dose Cytarabine for Previously Untreated Patients With Acute Myeloid Leukemia: Results From a Phase Ib/II Studybreakdown → | 2019 | 456 |
| 14 | 2019 | 39 | |
| 15 | 2018 | 254 | |
| 16 | 2018 | 86 | |
| 17 | 2018 | 20 | |
| 18 | 2018 | 157 | |
| 19 | 2017 | 112 | |
| 20 | 2016 | 16 |
About Michael R. Savona
Michael R. Savona is a scholar working on Hematology, Genetics and Molecular Biology, having authored 207 papers that have together received 4.3k indexed citations. Recurring topics across this work include Acute Myeloid Leukemia Research (100 papers), Myeloproliferative Neoplasms: Diagnosis and Treatment (43 papers), Chronic Myeloid Leukemia Treatments (43 papers), Chronic Lymphocytic Leukemia Research (39 papers), Acute Lymphoblastic Leukemia research (24 papers), Multiple Myeloma Research and Treatments (21 papers), Protein Degradation and Inhibitors (19 papers) and Histone Deacetylase Inhibitors Research (16 papers). The work is most often cited by research in Hematology (2.4k citations), Genetics (1.1k citations) and Virology (271 citations). Michael R. Savona has collaborated with scholars based in United States, Canada and Italy. Frequent co-authors include Moshe Talpaz, Stephen A. Strickland, Adewunmi Onafuwa-Nuga, Lucy A. McNamara, Kathleen L. Collins, James Riddell, Dale L. Bixby, Gail J. Roboz, Haley E. Ramsey and Maria P. Arrate. Their work appears in journals such as Proceedings of the National Academy of Sciences, JAMA and Nucleic Acids 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.