Andreas Genewsky

26 total papers · 874 total citations
18 papers, 504 citations indexed

About

Andreas Genewsky is a scholar working on Cellular and Molecular Neuroscience, Cognitive Neuroscience and Molecular Biology. According to data from OpenAlex, Andreas Genewsky has authored 18 papers receiving a total of 504 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Cellular and Molecular Neuroscience, 5 papers in Cognitive Neuroscience and 4 papers in Molecular Biology. Recurrent topics in Andreas Genewsky's work include Neuroscience and Neural Engineering (5 papers), Neuroscience and Neuropharmacology Research (4 papers) and Neural dynamics and brain function (3 papers). Andreas Genewsky is often cited by papers focused on Neuroscience and Neural Engineering (5 papers), Neuroscience and Neuropharmacology Research (4 papers) and Neural dynamics and brain function (3 papers). Andreas Genewsky collaborates with scholars based in Germany, United States and Brazil. Andreas Genewsky's co-authors include Marcel Leist, Tanja Waldmann, Dominik Pöltl, Diana Scholz, Stefan Schildknecht, Carsten T. Wotjak, Daniel E. Heinz, Paul M. Kaplick, Vivek Tanavde and Bastian Zimmer and has published in prestigious journals such as NeuroImage, Scientific Reports and Journal of Neurochemistry.

In The Last Decade

Andreas Genewsky

18 papers receiving 499 citations

Author Peers

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

Author						Papers	Cites
Andreas Genewsky	200	189	63	62	59	18	504
Verónica Anaya-Martı́nez	132 0.7×	194 1.0×	126 2.0×	62 1.0×	42 0.7×	19	475
Leticia Verdugo-Dı́az	102 0.5×	153 0.8×	41 0.7×	57 0.9×	143 2.4×	27	535
Gary J. Iacobucci	273 1.4×	242 1.3×	26 0.4×	31 0.5×	66 1.1×	25	553
Mireia Galofré	150 0.8×	202 1.1×	159 2.5×	49 0.8×	35 0.6×	27	518
Emanuele Brai	187 0.9×	97 0.5×	33 0.5×	52 0.8×	121 2.1×	18	524
Charles Marshall	175 0.9×	147 0.8×	41 0.7×	28 0.5×	185 3.1×	18	588
Lan Wang	162 0.8×	101 0.5×	55 0.9×	130 2.1×	40 0.7×	31	586
Jay‐Shake Li	144 0.7×	214 1.1×	27 0.4×	215 3.5×	101 1.7×	20	594
Christopher G. Langhammer	170 0.8×	195 1.0×	29 0.5×	33 0.5×	33 0.6×	19	477
Marcelo D. Rosato‐Siri	268 1.3×	312 1.7×	43 0.7×	60 1.0×	79 1.3×	17	481

Countries citing papers authored by Andreas Genewsky

Since Specialization

Citations

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

Fields of papers citing papers by Andreas Genewsky

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Andreas Genewsky

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