Tina Mainka

67 total papers · 1.6k total citations
43 papers, 664 citations indexed

About

Tina Mainka is a scholar working on Pharmacology, Neurology and Physiology. According to data from OpenAlex, Tina Mainka has authored 43 papers receiving a total of 664 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Pharmacology, 15 papers in Neurology and 13 papers in Physiology. Recurrent topics in Tina Mainka's work include Musculoskeletal pain and rehabilitation (10 papers), Pain Mechanisms and Treatments (10 papers) and Parkinson's Disease Mechanisms and Treatments (8 papers). Tina Mainka is often cited by papers focused on Musculoskeletal pain and rehabilitation (10 papers), Pain Mechanisms and Treatments (10 papers) and Parkinson's Disease Mechanisms and Treatments (8 papers). Tina Mainka collaborates with scholars based in Germany, United Kingdom and Italy. Tina Mainka's co-authors include Elena Enax‐Krumova, Christoph Maier, Jan Vollert, Ralf Baron, Rolf‐Detlef Treede, Christos Ganos, Carsten Buhmann, Claudia S. Maier, Andrea A. Kühn and Nathalie M. Malewicz and has published in prestigious journals such as Brain, Pain and International Journal of Molecular Sciences.

In The Last Decade

Tina Mainka

39 papers receiving 642 citations

Author Peers

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

Author Last Decade Papers Cites
Tina Mainka 325 226 206 123 97 43 664
Elena Enax‐Krumova 480 1.5× 304 1.3× 225 1.1× 168 1.4× 112 1.2× 54 775
Uwe Kern 200 0.6× 163 0.7× 113 0.5× 59 0.5× 52 0.5× 23 599
Philipp Hüllemann 437 1.3× 262 1.2× 170 0.8× 171 1.4× 76 0.8× 39 640
Julien Nizard 264 0.8× 108 0.5× 114 0.6× 127 1.0× 128 1.3× 58 728
Ming‐Tsung Tseng 391 1.2× 90 0.4× 259 1.3× 147 1.2× 54 0.6× 22 647
Pablo Andrade 152 0.5× 165 0.7× 190 0.9× 87 0.7× 57 0.6× 40 598
Andrew Clair 216 0.7× 295 1.3× 111 0.5× 153 1.2× 310 3.2× 35 689
Marcus Schley 409 1.3× 294 1.3× 72 0.3× 78 0.6× 75 0.8× 28 775
Natalie R. Osborne 334 1.0× 234 1.0× 79 0.4× 303 2.5× 146 1.5× 29 725
Masako Iseki 235 0.7× 128 0.6× 88 0.4× 63 0.5× 60 0.6× 68 568

Countries citing papers authored by Tina Mainka

Since Specialization
Citations

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

Fields of papers citing papers by Tina Mainka

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tina Mainka

This figure shows the co-authorship network connecting the top 25 collaborators of Tina Mainka. A scholar is included among the top collaborators of Tina Mainka 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 Tina Mainka. Tina Mainka 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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