David J. De Vries

23 total papers · 516 total citations
19 papers, 424 citations indexed

About

David J. De Vries is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Pharmacology. According to data from OpenAlex, David J. De Vries has authored 19 papers receiving a total of 424 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 8 papers in Cellular and Molecular Neuroscience and 3 papers in Pharmacology. Recurrent topics in David J. De Vries's work include Neuroscience and Neuropharmacology Research (6 papers), Neurotransmitter Receptor Influence on Behavior (5 papers) and Receptor Mechanisms and Signaling (5 papers). David J. De Vries is often cited by papers focused on Neuroscience and Neuropharmacology Research (6 papers), Neurotransmitter Receptor Influence on Behavior (5 papers) and Receptor Mechanisms and Signaling (5 papers). David J. De Vries collaborates with scholars based in Australia, United States and New Zealand. David J. De Vries's co-authors include Philip M. Beart, Peter M. Blumberg, Richard H. Willis, George R. Pettit, Cherry L. Herald, Michael R. Hall, Leigh C. Ward, B. C. Shanley, Marion Cincotta and Peter A. Wilce and has published in prestigious journals such as Trends in Pharmacological Sciences, Biochemical Pharmacology and Life Sciences.

In The Last Decade

David J. De Vries

19 papers receiving 391 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 J. De Vries 223 157 87 62 55 19 424
Shrinivasan Raghuraman 276 1.2× 118 0.8× 23 0.3× 89 1.4× 65 1.2× 29 463
Kazunori Ohta 204 0.9× 47 0.3× 50 0.6× 31 0.5× 137 2.5× 23 463
Jozi Godoy Figueiredo 135 0.6× 42 0.3× 39 0.4× 43 0.7× 70 1.3× 18 421
Xi-Lin Lu 145 0.7× 77 0.5× 16 0.2× 40 0.6× 91 1.7× 23 420
Soon-Youl Lee 175 0.8× 70 0.4× 84 1.0× 25 0.4× 108 2.0× 21 391
Manabu Takemura 168 0.8× 36 0.2× 17 0.2× 23 0.4× 65 1.2× 22 474
Pei-Chin Chen 106 0.5× 19 0.1× 79 0.9× 52 0.8× 53 1.0× 21 413
Helen Boyd 243 1.1× 109 0.7× 9 0.1× 36 0.6× 66 1.2× 19 492
Ken-ichi Nakajima 261 1.2× 54 0.3× 8 0.1× 32 0.5× 63 1.1× 19 407
S. Thomas Abraham 279 1.3× 104 0.7× 14 0.2× 21 0.3× 69 1.3× 21 433

Countries citing papers authored by David J. De Vries

Since Specialization
Citations

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

Fields of papers citing papers by David J. De Vries

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David J. De Vries. 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 J. De Vries. The network helps show where David J. De Vries may publish in the future.

Co-authorship network of co-authors of David J. De Vries

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