Nina Wronkowitz

874 total citations · 1 hit paper
7 papers, 741 citations indexed

About

Nina Wronkowitz is a scholar working on Endocrinology, Diabetes and Metabolism, Molecular Biology and Cellular and Molecular Neuroscience. According to data from OpenAlex, Nina Wronkowitz has authored 7 papers receiving a total of 741 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Endocrinology, Diabetes and Metabolism, 3 papers in Molecular Biology and 3 papers in Cellular and Molecular Neuroscience. Recurrent topics in Nina Wronkowitz's work include Diabetes Treatment and Management (4 papers), Neuropeptides and Animal Physiology (3 papers) and Peptidase Inhibition and Analysis (3 papers). Nina Wronkowitz is often cited by papers focused on Diabetes Treatment and Management (4 papers), Neuropeptides and Animal Physiology (3 papers) and Peptidase Inhibition and Analysis (3 papers). Nina Wronkowitz collaborates with scholars based in Germany, Belgium and Spain. Nina Wronkowitz's co-authors include Jürgen Eckel, Henrike Sell, D. Margriet Ouwens, Peter Arner, Susanne Famulla, Franz‐Georg Hanisch, Sonja Hartwig, Kristin Eckardt, Daniela Lamers and Johannes Ruige and has published in prestigious journals such as Diabetes, Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease and Journal of Hypertension.

In The Last Decade

Nina Wronkowitz

7 papers receiving 732 citations

Hit Papers

Dipeptidyl Peptidase 4 Is a Novel Adipokine Potentially L... 2011 2026 2016 2021 2011 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Nina Wronkowitz Germany 7 385 297 188 168 160 7 741
Stefan Müller Germany 4 281 0.7× 218 0.7× 188 1.0× 122 0.7× 229 1.4× 4 727
Megumi Kanasaki Japan 13 281 0.7× 190 0.6× 345 1.8× 64 0.4× 75 0.5× 27 890
Michishige Terasaki Japan 15 738 1.9× 125 0.4× 345 1.8× 141 0.8× 98 0.6× 45 1.1k
Vera Frison Italy 10 393 1.0× 128 0.4× 238 1.3× 60 0.4× 47 0.3× 17 537
P. M. van Koetsveld Netherlands 22 618 1.6× 276 0.9× 240 1.3× 52 0.3× 518 3.2× 41 1.2k
Bea Waser Switzerland 7 257 0.7× 207 0.7× 199 1.1× 73 0.4× 266 1.7× 7 671
Stephanie Oldham United States 15 246 0.6× 68 0.2× 281 1.5× 37 0.2× 373 2.3× 26 889
Victor Lavis United States 17 239 0.6× 196 0.7× 252 1.3× 32 0.2× 110 0.7× 41 775
Kikuko Amo Japan 7 221 0.6× 77 0.3× 276 1.5× 49 0.3× 144 0.9× 9 765
Xuesong Guan United States 11 1.3k 3.4× 279 0.9× 612 3.3× 59 0.4× 177 1.1× 21 1.7k

Countries citing papers authored by Nina Wronkowitz

Since Specialization
Citations

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

Fields of papers citing papers by Nina Wronkowitz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nina Wronkowitz

This figure shows the co-authorship network connecting the top 25 collaborators of Nina Wronkowitz. A scholar is included among the top collaborators of Nina Wronkowitz 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 Nina Wronkowitz. Nina Wronkowitz is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

7 of 7 papers shown
1.
Wronkowitz, Nina, Thorsten Hartmann, Sven W. Görgens, et al.. (2017). LAPS Insulin115 : A novel ultra‐long‐acting basal insulin with a unique action profile. Diabetes Obesity and Metabolism. 19(12). 1722–1731. 23 indexed citations
2.
Hartmann, Thorsten, D. Margriet Ouwens, Silja Raschke, et al.. (2016). Effect of the long-acting insulin analogues glargine and degludec on cardiomyocyte cell signalling and function. Cardiovascular Diabetology. 15(1). 96–96. 6 indexed citations
3.
Romacho, Tania, Susana Vallejo, Laura A. Villalobos, et al.. (2016). Soluble dipeptidyl peptidase-4 induces microvascular endothelial dysfunction through proteinase-activated receptor-2 and thromboxane A2 release. Journal of Hypertension. 34(5). 869–876. 43 indexed citations
4.
Wronkowitz, Nina, Sven W. Görgens, Tania Romacho, et al.. (2014). Soluble DPP4 induces inflammation and proliferation of human smooth muscle cells via protease-activated receptor 2. Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease. 1842(9). 1613–1621. 132 indexed citations
5.
Wronkowitz, Nina, Tania Romacho, Henrike Sell, & Jürgen Eckel. (2014). Adipose Tissue Dysfunction and Inflammation in Cardiovascular Disease. Frontiers of hormone research. 79–92. 31 indexed citations
6.
Wronkowitz, Nina, A. Cramer, Heidi Kaastrup Müller, et al.. (2013). Adipocyte-derived factors impair insulin signaling in differentiated human vascular smooth muscle cells via the upregulation of miR-143. Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease. 1842(2). 275–283. 25 indexed citations
7.
Lamers, Daniela, Susanne Famulla, Nina Wronkowitz, et al.. (2011). Dipeptidyl Peptidase 4 Is a Novel Adipokine Potentially Linking Obesity to the Metabolic Syndrome. Diabetes. 60(7). 1917–1925. 481 indexed citations breakdown →

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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