Fiona C. Brown
Impact in
- Hematology top 5%
- Acute Myeloid Leukemia Research
- Genetics top 10%
Papers in
-
- Protein Degradation and Inhibitors 4
- Hematology 10
- Acute Myeloid Leukemia Research 9
- Chronic Myeloid Leukemia Treatments 4
- Co-authors
- Alex Kentsis (5 shared papers)Elisa de Stanchina (2 shared papers)Marian C. Okondo (1 shared paper)Darren C. Johnson (1 shared paper)Ashley J. Chui (1 shared paper)Casie Reed (1 shared paper)Daniel A. Bachovchin (1 shared paper)Cornelius Y. Taabazuing (1 shared paper)
- Journals
- Blood (8 papers)Blood Advances (3 papers)British Journal of Haematology (2 papers)Disease Models & Mechanisms (2 papers)Nature Communications (2 papers)
- Partner nations
- AustraliaUnited StatesFrance
In The Last Decade
Fiona C. Brown
25 papers receiving 691 citations
Peers
Comparison fields: 5 of 64
- Hematology 260
- Genetics 99
- Immunology 146
- Molecular Biology 470
- Nephrology 41
Countries citing papers authored by Fiona C. Brown
This map shows the geographic impact of Fiona C. Brown'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 Fiona C. Brown with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fiona C. Brown more than expected).
Fields of papers citing papers by Fiona C. Brown
This network shows the impact of papers produced by Fiona C. Brown. 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 Fiona C. Brown. The network helps show where Fiona C. Brown may publish in the future.
Co-authors
The 25 scholars most cited alongside Fiona C. Brown, 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 | 2018 | 268 | |
| 2 | 2020 | 117 | |
| 3 | 2018 | 68 | |
| 4 | 2016 | 45 | |
| 5 | 2024 | 25 | |
| 6 | 2016 | 21 | |
| 7 | 2022 | 17 | |
| 8 | 2015 | 16 | |
| 9 | 2020 | 16 | |
| 10 | 2012 | 15 | |
| 11 | 2013 | 15 | |
| 12 | 2022 | 15 | |
| 13 | 2018 | 12 | |
| 14 | 2024 | 7 | |
| 15 | 2017 | 7 | |
| 16 | 1959 | 7 | |
| 17 | 2017 | 6 | |
| 18 | 2018 | 6 | |
| 19 | 2025 | 5 | |
| 20 | 2023 | 3 |
About Fiona C. Brown
Fiona C. Brown is a scholar working on Molecular Biology, Hematology, Genetics, Physiology and Oncology, having authored 27 papers that have together received 697 indexed citations. Recurring topics across this work include Acute Myeloid Leukemia Research (9 papers), Erythrocyte Function and Pathophysiology (5 papers), Hemoglobinopathies and Related Disorders (4 papers), Protein Degradation and Inhibitors (4 papers), Acute Lymphoblastic Leukemia research (4 papers), Chronic Myeloid Leukemia Treatments (4 papers), Chronic Lymphocytic Leukemia Research (3 papers) and Neonatal Health and Biochemistry (3 papers). The work is most often cited by research in Hematology (260 citations), Genetics (99 citations), Immunology (146 citations), Molecular Biology (470 citations) and Nephrology (41 citations). Fiona C. Brown has collaborated with scholars based in Australia, United States and France. Frequent co-authors include Alex Kentsis, Elisa de Stanchina, Marian C. Okondo, Darren C. Johnson, Ashley J. Chui, Casie Reed, Daniel A. Bachovchin, Cornelius Y. Taabazuing, Elizabeth Peguero and Sahana D. Rao. Their work appears in journals such as Blood, Blood Advances, British Journal of Haematology, Disease Models & Mechanisms and Nature Communications.
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.