Nadezhda German

64 total papers · 1.1k total citations
42 papers, 893 citations indexed

About

Nadezhda German is a scholar working on Molecular Biology, Pharmacology and Cellular and Molecular Neuroscience. According to data from OpenAlex, Nadezhda German has authored 42 papers receiving a total of 893 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Molecular Biology, 9 papers in Pharmacology and 6 papers in Cellular and Molecular Neuroscience. Recurrent topics in Nadezhda German's work include Cannabis and Cannabinoid Research (7 papers), Antibiotic Resistance in Bacteria (4 papers) and Trace Elements in Health (4 papers). Nadezhda German is often cited by papers focused on Cannabis and Cannabinoid Research (7 papers), Antibiotic Resistance in Bacteria (4 papers) and Trace Elements in Health (4 papers). Nadezhda German collaborates with scholars based in United States, China and Denmark. Nadezhda German's co-authors include Robert J. Kerns, Constantinos M. Mikelis, Christopher Rensing, Yanan Zhang, Glenn W. Kaatz, Fatema Tuz Zahra, Michail S. Lionakis, Brian F. Thomas, Ann M. Decker and Brian P. Gilmour and has published in prestigious journals such as The FASEB Journal, Journal of Controlled Release and Journal of Medicinal Chemistry.

In The Last Decade

Nadezhda German

40 papers receiving 884 citations

Author Peers

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

Author Last Decade Papers Cites
Nadezhda German 440 185 134 127 101 42 893
E. Kurt Dolence 409 0.9× 89 0.5× 169 1.3× 69 0.5× 201 2.0× 38 998
Tomomi Abe 264 0.6× 100 0.5× 62 0.5× 60 0.5× 53 0.5× 43 832
John K. Walker 479 1.1× 110 0.6× 214 1.6× 66 0.5× 192 1.9× 49 1.0k
Mehdi Rezaee 489 1.1× 149 0.8× 74 0.6× 52 0.4× 27 0.3× 32 1.0k
Qamre Alam 430 1.0× 85 0.5× 57 0.4× 104 0.8× 36 0.4× 51 1.0k
Shuai Guo 656 1.5× 78 0.4× 39 0.3× 114 0.9× 53 0.5× 75 1.0k
Erika Fornasari 376 0.9× 132 0.7× 45 0.3× 62 0.5× 151 1.5× 28 868
Sarika Gupta 315 0.7× 119 0.6× 41 0.3× 54 0.4× 64 0.6× 46 832
Claudia Banchio 571 1.3× 100 0.5× 35 0.3× 53 0.4× 31 0.3× 42 970
Naoki Sakura 483 1.1× 137 0.7× 147 1.1× 225 1.8× 97 1.0× 75 988

Countries citing papers authored by Nadezhda German

Since Specialization
Citations

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

Fields of papers citing papers by Nadezhda German

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nadezhda German

This figure shows the co-authorship network connecting the top 25 collaborators of Nadezhda German. A scholar is included among the top collaborators of Nadezhda German 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 Nadezhda German. Nadezhda German 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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2026