Nina Hanke

49 total papers · 1.3k total citations
40 papers, 1.1k citations indexed

About

Nina Hanke is a scholar working on Pharmacology, Molecular Biology and Endocrinology, Diabetes and Metabolism. According to data from OpenAlex, Nina Hanke has authored 40 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Pharmacology, 14 papers in Molecular Biology and 10 papers in Endocrinology, Diabetes and Metabolism. Recurrent topics in Nina Hanke's work include Pharmacogenetics and Drug Metabolism (16 papers), Drug Transport and Resistance Mechanisms (8 papers) and Hormonal Regulation and Hypertension (6 papers). Nina Hanke is often cited by papers focused on Pharmacogenetics and Drug Metabolism (16 papers), Drug Transport and Resistance Mechanisms (8 papers) and Hormonal Regulation and Hypertension (6 papers). Nina Hanke collaborates with scholars based in Germany, United States and United Kingdom. Nina Hanke's co-authors include Thorsten Lehr, Rolf W. Hartmann, Gerolf Gros, Renate Scheibe, Thomas Wendl, Sebastian Frechen, Hans‐Peter Kubis, Hannah Britz, Thomas Eißing and Paul J. Schechter and has published in prestigious journals such as PLoS ONE, Neurology and Journal of Medicinal Chemistry.

In The Last Decade

Nina Hanke

38 papers receiving 1.0k citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Nina Hanke 305 294 193 158 125 40 1.1k
David J. Freeman 161 0.5× 316 1.1× 181 0.9× 189 1.2× 107 0.9× 41 1.2k
Rhys Whomsley 210 0.7× 210 0.7× 153 0.8× 243 1.5× 145 1.2× 36 921
Karin Kramer Nielsen 384 1.3× 203 0.7× 163 0.8× 105 0.7× 130 1.0× 28 921
Scott Grimm 614 2.0× 254 0.9× 404 2.1× 159 1.0× 117 0.9× 50 1.3k
Ernesto Callegari 393 1.3× 419 1.4× 340 1.8× 157 1.0× 62 0.5× 29 1.3k
W Kalow 669 2.2× 263 0.9× 306 1.6× 168 1.1× 91 0.7× 35 1.1k
Sanjeev Kumar 235 0.8× 353 1.2× 220 1.1× 84 0.5× 157 1.3× 41 1.2k
Dongsheng Ouyang 485 1.6× 453 1.5× 186 1.0× 110 0.7× 55 0.4× 59 1.3k
Mitchell D. Green 582 1.9× 500 1.7× 322 1.7× 220 1.4× 42 0.3× 25 1.2k
Pollen Yeung 227 0.7× 237 0.8× 183 0.9× 121 0.8× 50 0.4× 82 1.1k

Countries citing papers authored by Nina Hanke

Since Specialization
Citations

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

Fields of papers citing papers by Nina Hanke

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nina Hanke

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

All Works

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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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