G. King Farrington

23 total papers · 1.0k total citations
19 papers, 845 citations indexed

About

G. King Farrington is a scholar working on Molecular Biology, Immunology and Agronomy and Crop Science. According to data from OpenAlex, G. King Farrington has authored 19 papers receiving a total of 845 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 5 papers in Immunology and 4 papers in Agronomy and Crop Science. Recurrent topics in G. King Farrington's work include T-cell and Retrovirus Studies (4 papers), Animal Disease Management and Epidemiology (4 papers) and Vector-Borne Animal Diseases (3 papers). G. King Farrington is often cited by papers focused on T-cell and Retrovirus Studies (4 papers), Animal Disease Management and Epidemiology (4 papers) and Vector-Borne Animal Diseases (3 papers). G. King Farrington collaborates with scholars based in United States, Austria and Switzerland. G. King Farrington's co-authors include Frederick C. Wedler, Joachim Hauber, Ernst Böhnlein, Barbara Wolff, F Hammerschmid, Michael Rühl, J R Rusche, David J. Merkler, Dorian Bevec and H.N. Aschauer and has published in prestigious journals such as Journal of Biological Chemistry, The Journal of Cell Biology and Accounts of Chemical Research.

In The Last Decade

G. King Farrington

18 papers receiving 803 citations

Author Peers

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

Author Last Decade Papers Cites
G. King Farrington 479 159 149 148 103 19 845
Todd Mayhood 591 1.2× 142 0.9× 87 0.6× 29 0.2× 41 0.4× 19 927
Joyce E. Jentoft 499 1.0× 34 0.2× 25 0.2× 145 1.0× 26 0.3× 36 846
Kay L. Nakamaye 582 1.2× 52 0.3× 100 0.7× 18 0.1× 20 0.2× 13 825
Azin Nezami 392 0.8× 85 0.5× 63 0.4× 19 0.1× 10 0.1× 15 769
Elisabetta Pilotti 215 0.4× 292 1.8× 143 1.0× 150 1.0× 85 0.8× 28 839
Klaus Bahl Andersen 460 1.0× 68 0.4× 15 0.1× 148 1.0× 9 0.1× 19 729
Dale C. Blomstrom 287 0.6× 296 1.9× 236 1.6× 79 0.5× 4 0.0× 19 877
Joachim Jaeger 470 1.0× 64 0.4× 29 0.2× 45 0.3× 10 0.1× 21 828
Jingwei Tang 727 1.5× 44 0.3× 89 0.6× 91 0.6× 10 0.1× 24 1.0k
Denis Bouvier 528 1.1× 221 1.4× 43 0.3× 122 0.8× 17 0.2× 16 1.0k

Countries citing papers authored by G. King Farrington

Since Specialization
Citations

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

Fields of papers citing papers by G. King Farrington

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by G. King Farrington. 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 G. King Farrington. The network helps show where G. King Farrington may publish in the future.

Co-authorship network of co-authors of G. King Farrington

This figure shows the co-authorship network connecting the top 25 collaborators of G. King Farrington. A scholar is included among the top collaborators of G. King Farrington 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 G. King Farrington. G. King Farrington 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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