Daniel D. Truong

49 total papers · 1.1k total citations
20 papers, 759 citations indexed

About

Daniel D. Truong is a scholar working on Neurology, Cellular and Molecular Neuroscience and Molecular Biology. According to data from OpenAlex, Daniel D. Truong has authored 20 papers receiving a total of 759 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Neurology, 7 papers in Cellular and Molecular Neuroscience and 4 papers in Molecular Biology. Recurrent topics in Daniel D. Truong's work include Neurological disorders and treatments (9 papers), Botulinum Toxin and Related Neurological Disorders (7 papers) and Neuroscience and Neuropharmacology Research (4 papers). Daniel D. Truong is often cited by papers focused on Neurological disorders and treatments (9 papers), Botulinum Toxin and Related Neurological Disorders (7 papers) and Neuroscience and Neuropharmacology Research (4 papers). Daniel D. Truong collaborates with scholars based in United States, Thailand and Netherlands. Daniel D. Truong's co-authors include Robert A. Hauser, Jean Hubble, Mark Stacy, Kelly E. Lyons, Stewart A. Factor, Bonnie Hersh, Nancy L. Earl, Rajesh Pahwa, Lawrence Elmer and Fabrizio Stocchi and has published in prestigious journals such as Neurology, Brain Research and Clinical Cancer Research.

In The Last Decade

Daniel D. Truong

19 papers receiving 743 citations

Author Peers

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

Author Last Decade Papers Cites
Daniel D. Truong 521 284 137 123 88 20 759
Monica Armida 266 0.5× 310 1.1× 188 1.4× 173 1.4× 62 0.7× 21 684
Akio Sekigawa 195 0.4× 263 0.9× 138 1.0× 220 1.8× 112 1.3× 18 740
Joseph Jankovic 388 0.7× 426 1.5× 28 0.2× 229 1.9× 43 0.5× 13 783
Raquel B. Dias 193 0.4× 361 1.3× 184 1.3× 278 2.3× 72 0.8× 16 825
Masaya Hashimoto 311 0.6× 151 0.5× 88 0.6× 102 0.8× 30 0.3× 30 694
J. Reiriz 231 0.4× 408 1.4× 45 0.3× 348 2.8× 31 0.4× 20 764
Donatienne Van Weehaeghe 324 0.6× 110 0.4× 94 0.7× 148 1.2× 60 0.7× 38 822
Patrick Hickey 511 1.0× 219 0.8× 29 0.2× 43 0.3× 146 1.7× 34 778
Nirosen Vijiaratnam 483 0.9× 219 0.8× 15 0.1× 169 1.4× 62 0.7× 41 795
Paul Robichaud 390 0.7× 91 0.3× 46 0.3× 203 1.7× 41 0.5× 17 662

Countries citing papers authored by Daniel D. Truong

Since Specialization
Citations

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

Fields of papers citing papers by Daniel D. Truong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel D. Truong. 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 Daniel D. Truong. The network helps show where Daniel D. Truong may publish in the future.

Co-authorship network of co-authors of Daniel D. Truong

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel D. Truong. A scholar is included among the top collaborators of Daniel D. Truong 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 Daniel D. Truong. Daniel D. Truong 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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