Jarl E. S. Wikberg

10.4k citations
234 papers · 9.1k · h-index 55

Impact in

Papers in

Jarl E. S. Wikberg

233 papers receiving 8.6k citations

Peers

Jarl E. S. Wikberg
Comparison fields: 5 of 140
  • Endocrine and Autonomic Systems 1.7k
  • Cellular and Molecular Neuroscience 2.2k
  • Computational Theory and Mathematics 1.3k
  • Molecular Biology 3.3k
  • Behavioral Neuroscience 101
Replace Anthony J. Harmar with:
Anthony J. Harmar United Kingdom
K. George Chandy United States
Richard R. Neubig United States
Zachary A. Knight United States
Oksana C. Palyha United States
Louis M. Luttrell United States
Joseph M. Metzger United States
Terry Kenakin United States
Evi Kostenis Germany
Markus Böhm Germany
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Citations per field
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Citations per year

Countries citing papers authored by Jarl E. S. Wikberg

Since Specialization
Citations

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

Fields of papers citing papers by Jarl E. S. Wikberg

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jarl E. S. Wikberg. 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 Jarl E. S. Wikberg. The network helps show where Jarl E. S. Wikberg may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 234 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1992546
2 1993306
3 2000286
4 1999164
5 1978152
6 1998145
7 1991133
8 1998127
9 1995125
10 2017121
11 1998118
12 2001114
13 2008108
14 1979106
15 1981103
16 197899
17 200796
18 199094
19 199891
20 200291

About Jarl E. S. Wikberg

Jarl E. S. Wikberg is a scholar working on Cellular and Molecular Neuroscience, Endocrine and Autonomic Systems, Computational Theory and Mathematics, Molecular Biology and Cell Biology, having authored 234 papers that have together received 9.1k indexed citations. Recurring topics across this work include Receptor Mechanisms and Signaling (73 papers), Computational Drug Discovery Methods (49 papers), Neuropeptides and Animal Physiology (46 papers), Regulation of Appetite and Obesity (34 papers), Chemical Synthesis and Analysis (15 papers), Phosphodiesterase function and regulation (11 papers), melanin and skin pigmentation (9 papers) and Neurotransmitter Receptor Influence on Behavior (7 papers). The work is most often cited by research in Endocrine and Autonomic Systems (1.7k citations), Cellular and Molecular Neuroscience (2.2k citations), Computational Theory and Mathematics (1.3k citations), Molecular Biology (3.3k citations) and Behavioral Neuroscience (101 citations). Jarl E. S. Wikberg has collaborated with scholars based in Sweden, Latvia and Thailand. Frequent co-authors include Vijay Chhajlani, Ruta Muceniece, Staffan Uhlén, Peteris Prūsis, Felikss Mutulis, Helgi Schiöth, Maris Lapins, Ilona Mandrika, Ants Kask and Ramona Petrovska. Their work appears in journals such as Biochemical and Biophysical Research Communications, European Journal of Pharmacology, BMC Bioinformatics, Peptides and British Journal of Pharmacology.

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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