Nina Geiger

21 total papers · 635 total citations
12 papers, 255 citations indexed

About

Nina Geiger is a scholar working on Infectious Diseases, Molecular Biology and Epidemiology. According to data from OpenAlex, Nina Geiger has authored 12 papers receiving a total of 255 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Infectious Diseases, 6 papers in Molecular Biology and 3 papers in Epidemiology. Recurrent topics in Nina Geiger's work include SARS-CoV-2 and COVID-19 Research (6 papers), COVID-19 Clinical Research Studies (3 papers) and Pharmacological Receptor Mechanisms and Effects (3 papers). Nina Geiger is often cited by papers focused on SARS-CoV-2 and COVID-19 Research (6 papers), COVID-19 Clinical Research Studies (3 papers) and Pharmacological Receptor Mechanisms and Effects (3 papers). Nina Geiger collaborates with scholars based in Germany, United States and Egypt. Nina Geiger's co-authors include Jochen Bodem, Katherina Sewald, Jürgen Seibel, Heike Oberwinkler, Maria Steinke, Olga Danov, Anke C. Schiedel, Lan Phuong Vu, Dominik Thimm and Michael Gütschow and has published in prestigious journals such as Nucleic Acids Research, Angewandte Chemie International Edition and Scientific Reports.

In The Last Decade

Nina Geiger

10 papers receiving 253 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 Geiger 124 119 73 42 38 12 255
Gi Uk Jeong 78 0.6× 118 1.0× 29 0.4× 81 1.9× 15 0.4× 13 283
Mohamed Mahdi 96 0.8× 124 1.0× 76 1.0× 12 0.3× 28 0.7× 26 262
Karen Anbro Gammeltoft 69 0.6× 185 1.6× 97 1.3× 19 0.5× 27 0.7× 9 280
Jyothi Padiadpu 176 1.4× 61 0.5× 30 0.4× 25 0.6× 22 0.6× 17 320
Senbao Lu 134 1.1× 143 1.2× 36 0.5× 14 0.3× 4 0.1× 8 297
Michael J. Capper 96 0.8× 17 0.1× 24 0.3× 36 0.9× 57 1.5× 8 237
Fuxing Lou 74 0.6× 177 1.5× 18 0.2× 20 0.5× 8 0.2× 10 307
Fahima Danesh Pouya 96 0.8× 143 1.2× 29 0.4× 44 1.0× 6 0.2× 14 298
Xiaolin Xie 89 0.7× 158 1.3× 108 1.5× 19 0.5× 56 1.5× 10 306
Robert Haupt 48 0.4× 142 1.2× 52 0.7× 22 0.5× 9 0.2× 6 205

Countries citing papers authored by Nina Geiger

Since Specialization
Citations

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

Fields of papers citing papers by Nina Geiger

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nina Geiger

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