Kate E. Brilliant
Impact in
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- MicroRNA in disease regulation
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- Extracellular vesicles in disease
- RNA Interference and Gene Delivery
- Circular RNAs in diseases
- Melanoma and MAPK Pathways
Papers in
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- Extracellular vesicles in disease 4
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- Liver physiology and pathology 5
- Hepatitis C virus research 2
- Co-authors
- Douglas C. Hixson (16 shared papers)Peter J. Quesenberry (4 shared papers)Bharat Ramratnam (2 shared papers)Mark S. Dooner (2 shared papers)Jason M. Aliotta (2 shared papers)Mandy Pereira (2 shared papers)Djuro Josić (4 shared papers)Carol A. Ayala (1 shared paper)
- Journals
- Experimental and Molecular Pathology (5 papers)PLoS ONE (2 papers)Electrophoresis (1 paper)Journal of Nanoparticle Research (1 paper)BMC Cancer (1 paper)
- Partner nations
- United StatesCroatiaItaly
In The Last Decade
Kate E. Brilliant
21 papers receiving 410 citations
Peers
Comparison fields: 5 of 72
- Cancer Research 150
- Molecular Biology 296
- Genetics 40
- Hepatology 29
- Immunology 47
Countries citing papers authored by Kate E. Brilliant
This map shows the geographic impact of Kate E. Brilliant'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 Kate E. Brilliant with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kate E. Brilliant more than expected).
Fields of papers citing papers by Kate E. Brilliant
This network shows the impact of papers produced by Kate E. Brilliant. 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 Kate E. Brilliant. The network helps show where Kate E. Brilliant may publish in the future.
Co-authors
The 25 scholars most cited alongside Kate E. Brilliant, 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 22 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2010 | 173 | |
| 2 | 2013 | 46 | |
| 3 | 2012 | 41 | |
| 4 | 2005 | 18 | |
| 5 | 2012 | 16 | |
| 6 | 2006 | 14 | |
| 7 | 2009 | 13 | |
| 8 | 2012 | 13 | |
| 9 | 2013 | 13 | |
| 10 | 2004 | 12 | |
| 11 | 2009 | 10 | |
| 12 | 2017 | 10 | |
| 13 | 2012 | 9 | |
| 14 | 2009 | 9 | |
| 15 | 2016 | 8 | |
| 16 | 2010 | 6 | |
| 17 | 2013 | 5 | |
| 18 | 2012 | 2 | |
| 19 | 2013 | 1 | |
| 20 | 2022 | 1 |
About Kate E. Brilliant
Kate E. Brilliant is a scholar working on Molecular Biology, Hepatology, Oncology, Surgery and Pulmonary and Respiratory Medicine, having authored 22 papers that have together received 421 indexed citations. Recurring topics across this work include Liver physiology and pathology (5 papers), Extracellular vesicles in disease (4 papers), Colorectal Cancer Treatments and Studies (3 papers), Radiopharmaceutical Chemistry and Applications (3 papers), interferon and immune responses (3 papers), Cancer Mechanisms and Therapy (3 papers), Monoclonal and Polyclonal Antibodies Research (3 papers) and Hepatitis C virus research (2 papers). The work is most often cited by research in Cancer Research (150 citations), Molecular Biology (296 citations), Genetics (40 citations), Hepatology (29 citations) and Immunology (47 citations). Kate E. Brilliant has collaborated with scholars based in United States, Croatia and Italy. Frequent co-authors include Douglas C. Hixson, Peter J. Quesenberry, Bharat Ramratnam, Mark S. Dooner, Jason M. Aliotta, Mandy Pereira, Djuro Josić, Carol A. Ayala, David Lee and David Berz. Their work appears in journals such as Experimental and Molecular Pathology, PLoS ONE, Electrophoresis, Journal of Nanoparticle Research and BMC Cancer.
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.