David A. Ruhl

20 total papers · 927 total citations
15 papers, 667 citations indexed

About

David A. Ruhl is a scholar working on Cellular and Molecular Neuroscience, Cognitive Neuroscience and Molecular Biology. According to data from OpenAlex, David A. Ruhl has authored 15 papers receiving a total of 667 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Cellular and Molecular Neuroscience, 5 papers in Cognitive Neuroscience and 4 papers in Molecular Biology. Recurrent topics in David A. Ruhl's work include Neuroscience and Neuropharmacology Research (5 papers), Lipid Membrane Structure and Behavior (3 papers) and Functional Brain Connectivity Studies (3 papers). David A. Ruhl is often cited by papers focused on Neuroscience and Neuropharmacology Research (5 papers), Lipid Membrane Structure and Behavior (3 papers) and Functional Brain Connectivity Studies (3 papers). David A. Ruhl collaborates with scholars based in United States, United Kingdom and Austria. David A. Ruhl's co-authors include Ronald A. Yeo, Andrew R. Mayer, Edwin R. Chapman, Flannery Merideth, Charles Gasparovic, Mollie A. Monnig, Robert J. Thoma, Michael P. Bogenschutz, Clay Williams and Ethan S. Lippmann and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and Journal of Neuroscience.

In The Last Decade

David A. Ruhl

15 papers receiving 651 citations

Author Peers

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

Author Last Decade Papers Cites
David A. Ruhl 207 164 150 132 118 15 667
Elif M. Sikoglu 173 0.8× 253 1.5× 112 0.7× 108 0.8× 134 1.1× 24 790
Jeffrey T. Cole 235 1.1× 77 0.5× 116 0.8× 174 1.3× 35 0.3× 15 694
D. Rushton 162 0.8× 246 1.5× 277 1.8× 54 0.4× 48 0.4× 20 791
Mary T. Joy 205 1.0× 65 0.4× 144 1.0× 114 0.9× 27 0.2× 13 710
S. Suda 108 0.5× 257 1.6× 285 1.9× 37 0.3× 144 1.2× 14 643
Xiaodi Lin 225 1.1× 174 1.1× 226 1.5× 211 1.6× 53 0.4× 13 620
Elise Gondard 121 0.6× 128 0.8× 260 1.7× 44 0.3× 48 0.4× 15 585
Gissel M. Perez 179 0.9× 219 1.3× 268 1.8× 186 1.4× 21 0.2× 27 695
Vanessa Douet 273 1.3× 108 0.7× 81 0.5× 34 0.3× 80 0.7× 24 748
Sirisha Pochareddy 388 1.9× 151 0.9× 140 0.9× 49 0.4× 32 0.3× 10 753

Countries citing papers authored by David A. Ruhl

Since Specialization
Citations

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

Fields of papers citing papers by David A. Ruhl

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David A. Ruhl. 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 David A. Ruhl. The network helps show where David A. Ruhl may publish in the future.

Co-authorship network of co-authors of David A. Ruhl

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