Bartley Brown
Impact in
- Endocrinology top 5%
- Vibrio bacteria research studies
- Health Informatics top 10%
Papers in
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- Ubiquitin and proteasome pathways 1
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- Radiomics and Machine Learning in Medical Imaging 2
- Foreign Body Medical Cases 1
- Medical Imaging Techniques and Applications 1
- Co-authors
- Thomas L. Casavant (6 shared papers)Maria de Fátima Bonaldo (3 shared papers)Todd E. Scheetz (4 shared papers)И. А. Королева (2 shared papers)Hakeem Almabrazi (3 shared papers)Edward G. Ruby (2 shared papers)Margaret McFall‐Ngai (2 shared papers)Marcelo B. Soares (3 shared papers)
- Journals
- Proceedings of the National Academy of Sciences (2 papers)PLoS ONE (2 papers)Journal of Bioinformatics and Computational Biology (1 paper)PeerJ (1 paper)Physiological Genomics (1 paper)
- Partner nations
- United StatesItalyNetherlands
In The Last Decade
Bartley Brown
13 papers receiving 370 citations
Peers
Comparison fields: 5 of 83
- Endocrinology 79
- Health Informatics 11
- Aging 6
- Ecology, Evolution, Behavior and Systematics 64
- Radiology, Nuclear Medicine and Imaging 65
Countries citing papers authored by Bartley Brown
This map shows the geographic impact of Bartley 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 Bartley Brown with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bartley Brown more than expected).
Fields of papers citing papers by Bartley Brown
This network shows the impact of papers produced by Bartley 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 Bartley Brown. The network helps show where Bartley Brown may publish in the future.
Co-authors
The 25 scholars most cited alongside Bartley 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
| # | Work | ||
|---|---|---|---|
| 1 | 2010 | 144 | |
| 2 | 2008 | 80 | |
| 3 | 2016 | 64 | |
| 4 | 2017 | 19 | |
| 5 | 2012 | 18 | |
| 6 | 2019 | 18 | |
| 7 | 2019 | 13 | |
| 8 | 2021 | 8 | |
| 9 | Urinothorax: a rare cause of pleural effusion. | 2012 | 7 |
| 10 | 2004 | 5 | |
| 11 | 2021 | 4 | |
| 12 | 2024 | 1 | |
| 13 | 2007 | 1 |
About Bartley Brown
Bartley Brown is a scholar working on Molecular Biology, Radiology, Nuclear Medicine and Imaging, Ecology, Evolution, Behavior and Systematics, Oncology and Genetics, having authored 13 papers that have together received 382 indexed citations. Recurring topics across this work include Vibrio bacteria research studies (2 papers), Radiomics and Machine Learning in Medical Imaging (2 papers), Cephalopods and Marine Biology (2 papers), Biomarkers in Disease Mechanisms (1 paper), Ubiquitin and proteasome pathways (1 paper), Foreign Body Medical Cases (1 paper), Advanced X-ray and CT Imaging (1 paper) and Medical Imaging Techniques and Applications (1 paper). The work is most often cited by research in Endocrinology (79 citations), Health Informatics (11 citations), Aging (6 citations), Ecology, Evolution, Behavior and Systematics (64 citations) and Radiology, Nuclear Medicine and Imaging (65 citations). Bartley Brown has collaborated with scholars based in United States, Italy and Netherlands. Frequent co-authors include Thomas L. Casavant, Maria de Fátima Bonaldo, Todd E. Scheetz, И. А. Королева, Hakeem Almabrazi, Edward G. Ruby, Margaret McFall‐Ngai, Marcelo B. Soares, Amy L. Schaefer and Andrew M. Wier. Their work appears in journals such as Proceedings of the National Academy of Sciences, PLoS ONE, Journal of Bioinformatics and Computational Biology, PeerJ and Physiological Genomics.
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.