E. Maerker

3.1k total citations · 1 hit paper
27 papers, 2.4k citations indexed

About

E. Maerker is a scholar working on Molecular Biology, Physiology and Endocrinology, Diabetes and Metabolism. According to data from OpenAlex, E. Maerker has authored 27 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Molecular Biology, 11 papers in Physiology and 9 papers in Endocrinology, Diabetes and Metabolism. Recurrent topics in E. Maerker's work include Metabolism, Diabetes, and Cancer (14 papers), Adipose Tissue and Metabolism (9 papers) and Diabetes Treatment and Management (8 papers). E. Maerker is often cited by papers focused on Metabolism, Diabetes, and Cancer (14 papers), Adipose Tissue and Metabolism (9 papers) and Diabetes Treatment and Management (8 papers). E. Maerker collaborates with scholars based in Germany and Netherlands. E. Maerker's co-authors include K. Rett, Hans Häring, Michael Stümvoll, Andreas Fritsche, W. Renn, Otto Tschritter, S. Matthäei, A. Volk, Claus Thamer and Harald Staiger and has published in prestigious journals such as Circulation, The Journal of Clinical Endocrinology & Metabolism and Diabetes Care.

In The Last Decade

E. Maerker

27 papers receiving 2.3k citations

Hit Papers

Association of increased intramyocellular lipid content w... 1999 2026 2008 2017 1999 100 200 300 400 500

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
E. Maerker Germany 17 1.2k 859 699 527 512 27 2.4k
Yolanta T. Kruszynska United Kingdom 25 1.1k 0.9× 987 1.1× 858 1.2× 246 0.5× 760 1.5× 55 2.5k
Ulrike Lössner Germany 37 1.4k 1.2× 1.7k 1.9× 1.1k 1.6× 565 1.1× 393 0.8× 81 3.7k
Cristiana E. Juge-Aubry Switzerland 22 1.1k 1.0× 1.2k 1.4× 1.1k 1.5× 492 0.9× 304 0.6× 29 2.9k
Yasuhiro Sumida Japan 28 723 0.6× 761 0.9× 699 1.0× 424 0.8× 711 1.4× 62 2.8k
R B Simsolo United States 16 761 0.7× 823 1.0× 357 0.5× 409 0.8× 330 0.6× 21 1.7k
Agnieszka Nikołajuk Poland 25 768 0.7× 629 0.7× 630 0.9× 251 0.5× 325 0.6× 89 2.1k
Rina Hemi Israel 25 860 0.7× 871 1.0× 1.2k 1.7× 191 0.4× 416 0.8× 69 2.9k
Akira Katsuki Japan 26 816 0.7× 826 1.0× 476 0.7× 370 0.7× 703 1.4× 37 2.4k
Christina Koutsari United States 24 1.1k 0.9× 591 0.7× 402 0.6× 371 0.7× 323 0.6× 37 1.6k
Eva Klimčáková France 27 1.3k 1.1× 898 1.0× 645 0.9× 392 0.7× 129 0.3× 37 2.1k

Countries citing papers authored by E. Maerker

Since Specialization
Citations

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

Fields of papers citing papers by E. Maerker

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of E. Maerker

This figure shows the co-authorship network connecting the top 25 collaborators of E. Maerker. A scholar is included among the top collaborators of E. Maerker based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with E. Maerker. E. Maerker is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Koch, Matthias, K. Rett, A. Volk, et al.. (2009). Amino acid polymorphism Gly 972 Arg in IRS-1 is not associated to lower clamp-derived insulin sensitivity in young healthy first degree relatives of patients with type 2 diabetes. Experimental and Clinical Endocrinology & Diabetes. 107(5). 318–322. 7 indexed citations
2.
Volk, A., W. Renn, D. Overkamp, et al.. (2009). Insulin Action and Secretion in healthy, glucose tolerant first degree relatives of patients with type 2 diabetes mellitus. Influence of body weight. Experimental and Clinical Endocrinology & Diabetes. 107(2). 140–147. 7 indexed citations
3.
Tschritter, Otto, Andreas Fritsche, Norbert Stefan, et al.. (2003). Increased insulin clearance in peroxisome proliferator-activated receptor γ2 Pro12Ala. Metabolism. 52(6). 778–783. 26 indexed citations
4.
Haap, Michael, E. Maerker, W. Renn, et al.. (2003). Insulin-Like Effect of Low-Dose Leptin on Glucose Transport in Langendorff Rat Hearts. Experimental and Clinical Endocrinology & Diabetes. 111(3). 139–145. 11 indexed citations
5.
Maerker, E., Michael Stümvoll, Reiner Lammers, et al.. (2003). Induction of adiponectin gene expression in human myotubes by an adiponectin-containing HEK293 cell culture supernatant. Diabetologia. 46(7). 956–960. 28 indexed citations
6.
Staiger, Harald, Otto Tschritter, Jürgen Machann, et al.. (2003). Relationship of Serum Adiponectin and Leptin Concentrations with Body Fat Distribution in Humans. Obesity Research. 11(3). 368–376. 203 indexed citations
7.
Fritsche, Andreas, Norbert Stefan, Otto Tschritter, et al.. (2002). Relationships Among Age, Proinsulin Conversion, and β-Cell Function in Nondiabetic Humans. Diabetes. 51(suppl_1). S234–S239. 65 indexed citations
8.
Thamer, Claus, A. Volk, E. Maerker, et al.. (2002). Evidence for Greater Oxidative Substrate Flexibility in Male Carriers of the Pro 12 Ala Polymorphism in PPARγ2. Hormone and Metabolic Research. 34(3). 132–136. 24 indexed citations
9.
Balletshofer, Bernd, Kilian Rittig, A. Volk, et al.. (2001). Impaired Non-Esterified Fatty Acid Suppression is Associated with Endothelial Dysfunction in Insulin Resistant Subjects. Hormone and Metabolic Research. 33(7). 428–431. 18 indexed citations
10.
Fritsche, Andreas, Walter Renn, Otto Tschritter, et al.. (2001). The Prevalent Gly1057Asp Polymorphism in the Insulin Receptor Substrate-2 Gene Is Not Associated with Impaired Insulin Secretion. The Journal of Clinical Endocrinology & Metabolism. 86(10). 4822–4825. 24 indexed citations
11.
Jacob, Simon N., Michael Stümvoll, Roland Becker, et al.. (2000). The PPARγ2 Polymorphism Pro12Ala is Associated with Better Insulin Sensitivity in the Offspring of Type 2 Diabetic Patients. Hormone and Metabolic Research. 32(10). 413–416. 51 indexed citations
15.
Jacob, Simon N., Peter Ruus, Róbert Hermann, et al.. (1999). Oral administration of rac-α-lipoic acid modulates insulin sensitivity in patients with type-2 diabetes mellitus: a placebo-controlled pilot trial. Free Radical Biology and Medicine. 27(3-4). 309–314. 218 indexed citations
16.
Rett, K., et al.. (1997). Perfusion-Independent Effect of Bradykinin and Fosinoprilate on Glucose Transport in Langendorff Rat Hearts. The American Journal of Cardiology. 80(3). 143A–147A. 14 indexed citations
17.
Maerker, E., et al.. (1994). Insulin-induced translocation of GLUT 4 in skeletal muscle of insulin-resistant Zucker rats. Diabetologia. 37(1). 3–9. 14 indexed citations
18.
Rett, K., M. Wicklmayr, Edwin Fink, et al.. (1989). Local Generation of Kinins in Working Skeletal Muscle Tissue in Man. Biological Chemistry Hoppe-Seyler. 370(1). 445–450. 14 indexed citations
19.
Rett, K., et al.. (1986). Effects of Kallikrein (K), Bradykinin (B) and Insulin (I), on Substrate Metabolism in the Isolated Perfused Rat Heart. Advances in experimental medicine and biology. 198 Pt B. 379–384. 5 indexed citations
20.
Dietze, G., E. Maerker, M. Wicklmayr, et al.. (1984). Possible Involvement of Kinins in Muscle Energy Metabolism. Advances in experimental medicine and biology. 167. 63–71. 14 indexed citations

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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