Daniel J. DeAngelo
- Hematology top 0.02%
- Acute Myeloid Leukemia Research 168
- Chronic Myeloid Leukemia Treatments 119
- Genetics top 0.1%
- Chronic Lymphocytic Leukemia Research 83
- Oncology top 0.5%
- CAR-T cell therapy research 64
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- Acute Lymphoblastic Leukemia research 146
- Molecular Biology top 0.5%
- Histone Deacetylase Inhibitors Research 39
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- Eosinophilic Disorders and Syndromes 41
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- Childhood Cancer Survivors' Quality of Life 38
- Co-authors
- Richard M. StoneMartha WadleighIlene GalinskyAnjali S. AdvaniWendy StockDonna NeubergHagop M. KantarjianRobert J. Soiffer
- Cited by
- HematologyGeneticsOncology
- Partner nations
- United StatesGermanyUnited Kingdom
In The Last Decade
Daniel J. DeAngelo
430 papers receiving 16.1k citations
Hit Papers
Peers
Comparison fields: 5 of 135
- Hematology 9.0k
- Genetics 3.9k
- Oncology 4.3k
- Public Health, Environmental and Occupational Health 4.3k
- Molecular Biology 6.2k
Countries citing papers authored by Daniel J. DeAngelo
This map shows the geographic impact of Daniel J. DeAngelo'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 Daniel J. DeAngelo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel J. DeAngelo more than expected).
Fields of papers citing papers by Daniel J. DeAngelo
This network shows the impact of papers produced by Daniel J. DeAngelo. 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 Daniel J. DeAngelo. The network helps show where Daniel J. DeAngelo may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Daniel J. DeAngelo, 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 | 1 | |
| 2 | 2025 | 2 | |
| 3 | 2024 | 5 | |
| 4 | 2024 | 0 | |
| 5 | 2024 | 1 | |
| 6 | 2024 | 1 | |
| 7 | 2024 | 1 | |
| 8 | 2024 | 14 | |
| 9 | 2023 | 3 | |
| 10 | 2023 | 2 | |
| 11 | 2021 | 29 | |
| 12 | 2021 | 1 | |
| 13 | 2021 | 88 | |
| 14 | 2020 | 27 | |
| 15 | Results from PIONEER: A randomized, double-blind, placebo-controlled, phase 2 study of avapritinib in patients with indolent systemic mastocytosis (ISM) | 2020 | 1 |
| 16 | 2019 | 23 | |
| 17 | 2018 | 10 | |
| 18 | 2014 | 190 | |
| 19 | 2013 | 79 | |
| 20 | 2010 | 102 |
About Daniel J. DeAngelo
Daniel J. DeAngelo is a scholar working on Hematology, Genetics and Public Health, Environmental and Occupational Health, having authored 444 papers that have together received 16.3k indexed citations. Recurring topics across this work include Acute Myeloid Leukemia Research (168 papers), Acute Lymphoblastic Leukemia research (146 papers), Chronic Myeloid Leukemia Treatments (119 papers), Chronic Lymphocytic Leukemia Research (83 papers), CAR-T cell therapy research (64 papers), Eosinophilic Disorders and Syndromes (41 papers), Histone Deacetylase Inhibitors Research (39 papers) and Childhood Cancer Survivors' Quality of Life (38 papers). The work is most often cited by research in Hematology (9.0k citations), Genetics (3.9k citations) and Oncology (4.3k citations). Daniel J. DeAngelo has collaborated with scholars based in United States, Germany and United Kingdom. Frequent co-authors include Richard M. Stone, Martha Wadleigh, Ilene Galinsky, Anjali S. Advani, Wendy Stock, Donna Neuberg, Hagop M. Kantarjian, Robert J. Soiffer, D. Gary Gilliland and Erik Vandendries. Their work appears in journals such as Blood, Journal of Clinical Oncology, Leukemia, American Journal 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.