Danielle M. Brander
Impact in
- Genetics top 1%
- Chronic Lymphocytic Leukemia Research
-
- Lymphoma Diagnosis and Treatment
Papers in
- Genetics 82
- Chronic Lymphocytic Leukemia Research 82
-
- Lymphoma Diagnosis and Treatment 28
- Co-authors
- Ian W. Flinn (16 shared papers)Peter Sportelli (11 shared papers)Andrea Sitlinger (15 shared papers)Hari P. Miskin (12 shared papers)David B. Bartlett (6 shared papers)Anthony R. Mato (22 shared papers)Howard A. Burris (6 shared papers)Owen A. O’Connor (6 shared papers)
- Journals
- Blood (34 papers)Journal of Clinical Oncology (15 papers)Blood Advances (4 papers)HemaSphere (4 papers)Hematological Oncology (2 papers)
- Partner nations
- United StatesAustraliaUnited Kingdom
In The Last Decade
Danielle M. Brander
81 papers receiving 961 citations
Peers
Comparison fields: 5 of 67
- Genetics 698
- Pathology and Forensic Medicine 450
- Hematology 183
- Immunology 172
- Oncology 185
Countries citing papers authored by Danielle M. Brander
This map shows the geographic impact of Danielle M. Brander'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 Danielle M. Brander with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Danielle M. Brander more than expected).
Fields of papers citing papers by Danielle M. Brander
This network shows the impact of papers produced by Danielle M. Brander. 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 Danielle M. Brander. The network helps show where Danielle M. Brander may publish in the future.
Co-authors
The 25 scholars most cited alongside Danielle M. Brander, 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 90 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 167 | |
| 2 | 2020 | 59 | |
| 3 | 2015 | 46 | |
| 4 | 2020 | 44 | |
| 5 | 2021 | 39 | |
| 6 | 2014 | 38 | |
| 7 | 2022 | 32 | |
| 8 | 2017 | 27 | |
| 9 | 2021 | 26 | |
| 10 | 2013 | 24 | |
| 11 | 2021 | 23 | |
| 12 | 2015 | 22 | |
| 13 | 2019 | 21 | |
| 14 | 2017 | 20 | |
| 15 | 2023 | 18 | |
| 16 | 2016 | 17 | |
| 17 | 2021 | 16 | |
| 18 | 2021 | 15 | |
| 19 | 2014 | 15 | |
| 20 | 2016 | 14 |
About Danielle M. Brander
Danielle M. Brander is a scholar working on Genetics, Pathology and Forensic Medicine, Pulmonary and Respiratory Medicine, Immunology and Hematology, having authored 90 papers that have together received 971 indexed citations. Recurring topics across this work include Chronic Lymphocytic Leukemia Research (82 papers), Lymphoma Diagnosis and Treatment (28 papers), Advanced Breast Cancer Therapies (17 papers), Immunodeficiency and Autoimmune Disorders (15 papers), Chronic Myeloid Leukemia Treatments (8 papers), Acute Myeloid Leukemia Research (6 papers), Acute Lymphoblastic Leukemia research (6 papers) and PI3K/AKT/mTOR signaling in cancer (4 papers). The work is most often cited by research in Genetics (698 citations), Pathology and Forensic Medicine (450 citations), Hematology (183 citations), Immunology (172 citations) and Oncology (185 citations). Danielle M. Brander has collaborated with scholars based in United States, Australia and United Kingdom. Frequent co-authors include Ian W. Flinn, Peter Sportelli, Andrea Sitlinger, Hari P. Miskin, David B. Bartlett, Anthony R. Mato, Howard A. Burris, Owen A. O’Connor, John G. Kuhn and Manish R. Patel. Their work appears in journals such as Blood, Journal of Clinical Oncology, Blood Advances, HemaSphere and Hematological Oncology.
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.