Stephen Brown
Impact in
- Rheumatology top 5%
- GDF15 and Related Biomarkers
-
- Macrophage Migration Inhibitory Factor
Papers in
-
- Epigenetics and DNA Methylation 2
- Developmental Biology and Gene Regulation 2
- TGF-β signaling in diseases 1
- Genetics 2
- Connective tissue disorders research 1
- Genetic and Kidney Cyst Diseases 1
- Co-authors
- Ling Qiu (1 shared paper)James A. Knowles (1 shared paper)Marcelo B. Soares (1 shared paper)Pierre C. Jelenc (1 shared paper)Dorothy Warburton (1 shared paper)Lee N. Lawton (1 shared paper)Maria de Fátima Bonaldo (1 shared paper)M. Ali Ansari‐Lari (1 shared paper)
- Journals
- Gene (2 papers)Frontiers in Neuroanatomy (1 paper)Fetal Diagnosis and Therapy (1 paper)Prenatal Diagnosis (1 paper)Journal of Visualized Experiments (1 paper)
- Partner nations
- United StatesLebanonUnited Kingdom
In The Last Decade
Stephen Brown
8 papers receiving 246 citations
Peers
Comparison fields: 5 of 45
- Rheumatology 168
- Immunology 114
- Physiology 99
- Cellular and Molecular Neuroscience 45
- Molecular Biology 89
Countries citing papers authored by Stephen Brown
This map shows the geographic impact of Stephen 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 Stephen Brown with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stephen Brown more than expected).
Fields of papers citing papers by Stephen Brown
This network shows the impact of papers produced by Stephen 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 Stephen Brown. The network helps show where Stephen Brown may publish in the future.
Co-authors
The 25 scholars most cited alongside Stephen 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 | 1997 | 182 | |
| 2 | 1998 | 20 | |
| 3 | 2014 | 15 | |
| 4 | 2009 | 13 | |
| 5 | 2009 | 7 | |
| 6 | 2017 | 6 | |
| 7 | 2003 | 4 | |
| 8 | 2017 | 2 |
About Stephen Brown
Stephen Brown is a scholar working on Molecular Biology, Genetics, Infectious Diseases, Genetics and Cardiology and Cardiovascular Medicine, having authored 8 papers that have together received 249 indexed citations. Recurring topics across this work include Epigenetics and DNA Methylation (2 papers), Developmental Biology and Gene Regulation (2 papers), Metabolism and Genetic Disorders (1 paper), Connective tissue disorders research (1 paper), TGF-β signaling in diseases (1 paper), Genetic and Kidney Cyst Diseases (1 paper), Biochemical Analysis and Sensing Techniques (1 paper) and Parvovirus B19 Infection Studies (1 paper). The work is most often cited by research in Rheumatology (168 citations), Immunology (114 citations), Physiology (99 citations), Cellular and Molecular Neuroscience (45 citations) and Molecular Biology (89 citations). Stephen Brown has collaborated with scholars based in United States, Lebanon and United Kingdom. Frequent co-authors include Ling Qiu, James A. Knowles, Marcelo B. Soares, Pierre C. Jelenc, Dorothy Warburton, Lee N. Lawton, Maria de Fátima Bonaldo, M. Ali Ansari‐Lari, Kirsten M. Timms and Richard A. Gibbs. Their work appears in journals such as Gene, Frontiers in Neuroanatomy, Fetal Diagnosis and Therapy, Prenatal Diagnosis and Journal of Visualized Experiments.
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.