G. P. Brown

19 papers receiving 651 citations

Peers

G. P. Brown
Comparison fields: 5 of 80
  • Obstetrics and Gynecology 81
  • Cardiology and Cardiovascular Medicine 191
  • Endocrinology, Diabetes and Metabolism 103
  • Biochemistry 36
  • Physiology 112
Replace R. Staffolani with:
R. Staffolani Italy
Duncan J. Campbell Australia
Tadashi Konoshita Japan
O. Saijonmaa Finland
Rudolf M. Snajdar United States
Philipp Kalk Germany
Anna Wickman Sweden
Liliya M. Yamaleyeva United States
Thiemo Pfab Germany
J R Ingelfinger United States
G. P. Brown relative to R. Staffolani Italy R. Staffolani's profile →
Citations per field
00.5×3.0×
R. Staffolani · 1×
Citations per year

Countries citing papers authored by G. P. Brown

Since Specialization
Citations

This map shows the geographic impact of G. P. 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 G. P. Brown with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites G. P. Brown more than expected).

Fields of papers citing papers by G. P. Brown

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by G. P. 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 G. P. Brown. The network helps show where G. P. Brown may publish in the future.

Co-authors

The 13 scholars most cited alongside G. P. Brown, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with G. P. Brown Line = papers co-authored together G. P. Brown links everyone, so they are left out of the graph.

All Works

19 of 19 papers shown
#Work
1 1988149
2 1989144
3 198281
4 198371
5 199252
6 198841
7 198241
8 198624
9 198421
10 19919
11 19889
12 19909
13 19985
14 19904
15 19873
16 20022
17 19882
18
Biochemical characterization of kappa-1 opiate binding sites in R11 thymoma cells
19931
19 19961

About G. P. Brown

G. P. Brown is a scholar working on Cardiology and Cardiovascular Medicine, Molecular Biology, Obstetrics and Gynecology, Pulmonary and Respiratory Medicine and Physiology, having authored 19 papers that have together received 669 indexed citations. Recurring topics across this work include Renin-Angiotensin System Studies (6 papers), Pregnancy and preeclampsia studies (5 papers), Receptor Mechanisms and Signaling (5 papers), Eicosanoids and Hypertension Pharmacology (4 papers), Ion Transport and Channel Regulation (3 papers), Hormonal Regulation and Hypertension (3 papers), Nitric Oxide and Endothelin Effects (2 papers) and Renal and Vascular Pathologies (2 papers). The work is most often cited by research in Obstetrics and Gynecology (81 citations), Cardiology and Cardiovascular Medicine (191 citations), Endocrinology, Diabetes and Metabolism (103 citations), Biochemistry (36 citations) and Physiology (112 citations). G. P. Brown has collaborated with scholars based in United States and Hungary. Frequent co-authors include Janice G. Douglas, M. M. Monick, Gary W. Hunninghake, Rocco C. Venuto, Gary K. Iwamoto, György Losonczy, Brian M. Murray, Marion Schoenl, J G Douglas and Zoltán Ungvári. Their work appears in journals such as American Journal of Physiology-Endocrinology and Metabolism, Endocrinology, American Journal of Physiology-Renal Physiology, Hypertension in Pregnancy and American Journal of Physiology-Cell Physiology.

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.

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