U. Schwabe

838 citations
45 papers · 569 · h-index 12

Impact in

    • Metabolism and Genetic Disorders
  • Physiology top 5%
    • Adipose Tissue and Metabolism
    • Diet and metabolism studies
    • Adenosine and Purinergic Signaling

Papers in

U. Schwabe

44 papers receiving 534 citations

Peers

U. Schwabe
Comparison fields: 5 of 69
  • Clinical Biochemistry 98
  • Physiology 59
  • Biochemistry 83
  • Physiology 251
  • Pharmacology 44
Replace J. G. T. Sneyd with:
J. G. T. Sneyd New Zealand
Changju Song United States
F D Assimacopoulos-Jeannet United States
David Saggerson United Kingdom
J H Exton United States
Juan E. Felı́u Spain
Hans‐Peter Bär Canada
Erela Gorin Israel
R. Fanska United States
Nellie Taleux France
U. Schwabe relative to J. G. T. Sneyd New Zealand J. G. T. Sneyd's profile →
Citations per field
00.5×
J. G. T. Sneyd · 1×
Citations per year

Countries citing papers authored by U. Schwabe

Since Specialization
Citations

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

Fields of papers citing papers by U. Schwabe

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by U. Schwabe. 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 U. Schwabe. The network helps show where U. Schwabe may publish in the future.

Co-authors

The 25 scholars most cited alongside U. Schwabe, 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 U. Schwabe Line = papers co-authored together U. Schwabe links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 45 papers — load more, or switch the sort, to bring in the rest.

#Work
1 197882
2 198466
3 198465
4
Adenosine release from fat cells: effect on cyclic AMP levels and hormone actions.
197557
5 198351
6 196822
7 196420
8 199120
9 198218
10 198615
11 199014
12 198011
13 198011
14 19669
15 19669
16 19679
17 19608
18 19606
19 19686
20 19756

About U. Schwabe

U. Schwabe is a scholar working on Physiology, Molecular Biology, Biochemistry, Organic Chemistry and Pharmacology, having authored 45 papers that have together received 569 indexed citations. Recurring topics across this work include Diet and metabolism studies (7 papers), Adipose Tissue and Metabolism (4 papers), Pharmacogenetics and Drug Metabolism (4 papers), Metabolism and Genetic Disorders (4 papers), Pharmacological Effects and Assays (4 papers), Cannabis and Cannabinoid Research (3 papers), Eicosanoids and Hypertension Pharmacology (3 papers) and Biochemical Acid Research Studies (3 papers). The work is most often cited by research in Clinical Biochemistry (98 citations), Physiology (59 citations), Biochemistry (83 citations), Physiology (251 citations) and Pharmacology (44 citations). U. Schwabe has collaborated with scholars based in Germany and United States. Frequent co-authors include Roland W. Scholz, Sibylle Soboll, A. Hasselblatt, Regina Ebert, Merle S. Olson, Karl‐Norbert Klotz, Andreas Schwab, Wolfgang Braun, Martin J. Lohse and Rainer Kimmig. Their work appears in journals such as Naunyn-Schmiedeberg s Archives of Pharmacology, European Journal of Biochemistry, Molecular Pharmacology, Journal of Molecular Medicine and Biochemistry.

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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