Daniel V. Brown
Impact in
- Health Informatics top 10%
- Genetics top 10%
- Glioma Diagnosis and Treatment
Papers in ⓘ
-
- Single-cell and spatial transcriptomics 3
- Genomics and Chromatin Dynamics 2
- Metabolomics and Mass Spectrometry Studies 2
- Oncology 9
- Cancer Cells and Metastasis 6
- Co-authors
- Theo Mantamadiotis (6 shared papers)Paul Daniel (4 shared papers)Andrew Morokoff (3 shared papers)Wayne Ng (2 shared papers)Gulay Filiz (3 shared papers)Giovanna M. D’Abaco (2 shared papers)Frédéric Hollande (2 shared papers)Grant A. McArthur (3 shared papers)
- Journals
- Nature Cell Biology (2 papers)Nucleic Acids Research (2 papers)Cancer Research (2 papers)Molecular Cancer Therapeutics (1 paper)Frontiers in bioscience (1 paper)
- Partner nations
- AustraliaUnited KingdomUnited States
In The Last Decade
Daniel V. Brown
27 papers receiving 835 citations
Peers
Comparison fields: 5 of 130
- Health Informatics 21
- Genetics 146
- Cancer Research 152
- Oncology 275
- Molecular Biology 437
Countries citing papers authored by Daniel V. Brown
This map shows the geographic impact of Daniel V. 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 Daniel V. Brown with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel V. Brown more than expected).
Fields of papers citing papers by Daniel V. Brown
This network shows the impact of papers produced by Daniel V. 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 Daniel V. Brown. The network helps show where Daniel V. Brown may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel V. 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 29 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 109 | |
| 2 | 2017 | 107 | |
| 3 | 2014 | 83 | |
| 4 | 2015 | 81 | |
| 5 | 2010 | 76 | |
| 6 | 2011 | 62 | |
| 7 | 2023 | 48 | |
| 8 | 2019 | 45 | |
| 9 | 1997 | 44 | |
| 10 | 2019 | 28 | |
| 11 | 2018 | 28 | |
| 12 | 2021 | 27 | |
| 13 | 2018 | 24 | |
| 14 | 1985 | 23 | |
| 15 | 1974 | 18 | |
| 16 | 2019 | 12 | |
| 17 | 1957 | 11 | |
| 18 | 2022 | 8 | |
| 19 | 2014 | 7 | |
| 20 | Results of Current Measurements with Drogues, 1963-1964. | 1965 | 5 |
About Daniel V. Brown
Daniel V. Brown is a scholar working on Molecular Biology, Oncology, Cancer Research, Genetics and Aerospace Engineering, having authored 29 papers that have together received 859 indexed citations. Recurring topics across this work include Cancer Cells and Metastasis (6 papers), Glioma Diagnosis and Treatment (4 papers), Single-cell and spatial transcriptomics (3 papers), MicroRNA in disease regulation (3 papers), Genomics and Chromatin Dynamics (2 papers), Ovarian cancer diagnosis and treatment (2 papers), Metabolomics and Mass Spectrometry Studies (2 papers) and T-cell and B-cell Immunology (2 papers). The work is most often cited by research in Health Informatics (21 citations), Genetics (146 citations), Cancer Research (152 citations), Oncology (275 citations) and Molecular Biology (437 citations). Daniel V. Brown has collaborated with scholars based in Australia, United Kingdom and United States. Frequent co-authors include Theo Mantamadiotis, Paul Daniel, Andrew Morokoff, Wayne Ng, Gulay Filiz, Giovanna M. D’Abaco, Frédéric Hollande, Grant A. McArthur, Andrew Gogos and Sebastian Dworkin. Their work appears in journals such as Nature Cell Biology, Nucleic Acids Research, Cancer Research, Molecular Cancer Therapeutics and Frontiers in bioscience.
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.