Agneta Mode

4.0k citations
92 papers · 3.4k indexed · h-index 33

Impact in

Papers in

Agneta Mode

92 papers receiving 3.3k citations

Peers

Agneta Mode
Comparison fields: 5 of 106
  • Pharmacology 927
  • Endocrinology, Diabetes and Metabolism 1.7k
  • Endocrine and Autonomic Systems 260
  • Biochemistry 222
  • Genetics 610
Replace Ann Marie Zavacki with:
Ann Marie Zavacki United States
Taira Wada Japan
Mohammed Qatanani United States
Dieter Schmoll Germany
Arthur R. Buckley United States
John M. Stafford United States
Marion B. Sewer United States
Bernard H. Shapiro United States
Xunshan Ding United States
Yonggong Zhai China
Agneta Mode relative to Ann Marie Zavacki United States Ann Marie Zavacki's profile →
Citations per field
00.5×3.4×
Ann Marie Zavacki · 1×
Citations per year

Countries citing papers authored by Agneta Mode

Since Specialization
Citations

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

Fields of papers citing papers by Agneta Mode

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 92 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1983270
2 1982150
3 1985143
4 1981140
5 2009136
6 1992125
7 1992125
8 1989115
9 1990111
10 199896
11 199792
12 200683
13 198876
14 199258
15 198952
16 199851
17 199149
18 200444
19 200844
20 198942

About Agneta Mode

Agneta Mode is a scholar working on Endocrinology, Diabetes and Metabolism, Pharmacology, Behavioral Neuroscience, Endocrine and Autonomic Systems and Cancer Research, having authored 92 papers that have together received 3.4k indexed citations. Recurring topics across this work include Growth Hormone and Insulin-like Growth Factors (47 papers), Hormonal Regulation and Hypertension (24 papers), Pharmacogenetics and Drug Metabolism (19 papers), Hormonal and reproductive studies (12 papers), Diet and metabolism studies (11 papers), Peroxisome Proliferator-Activated Receptors (10 papers), Cholesterol and Lipid Metabolism (10 papers) and Cancer, Hypoxia, and Metabolism (8 papers). The work is most often cited by research in Pharmacology (927 citations), Endocrinology, Diabetes and Metabolism (1.7k citations), Endocrine and Autonomic Systems (260 citations), Biochemistry (222 citations) and Genetics (610 citations). Agneta Mode has collaborated with scholars based in Sweden, United States and United Kingdom. Frequent co-authors include Jan-Ακε Gustafsson, Gunnar Norstedt, Catherine Legraverend, Paul Skett, P. Eneroth, Peter G. Zaphiropoulos, Petra Tollet, Anders Ström, Olle Isaksson and Timothy Wells. Their work appears in journals such as Endocrinology, Molecular Endocrinology, Journal of Endocrinology, Molecular and Cellular Endocrinology and Molecular 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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