Sac-Pham Tang

16 total papers · 470 total citations
9 papers, 357 citations indexed

About

Sac-Pham Tang is a scholar working on Molecular Biology, Pharmacology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Sac-Pham Tang has authored 9 papers receiving a total of 357 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Molecular Biology, 3 papers in Pharmacology and 3 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Sac-Pham Tang's work include Neurotransmitter Receptor Influence on Behavior (2 papers), Drug Transport and Resistance Mechanisms (2 papers) and Treatment of Major Depression (2 papers). Sac-Pham Tang is often cited by papers focused on Neurotransmitter Receptor Influence on Behavior (2 papers), Drug Transport and Resistance Mechanisms (2 papers) and Treatment of Major Depression (2 papers). Sac-Pham Tang collaborates with scholars based in United Kingdom, Denmark and United States. Sac-Pham Tang's co-authors include Alexander J. Stevens, Anne Hersey, David J. Spalding, Beverley Hammond, Roger N. Gunn, Lisa Wells, Scott Summerfield, Leanne Cutler, Phil Jeffrey and Martin R. Wilkins and has published in prestigious journals such as Journal of Pharmacology and Experimental Therapeutics, Journal of Cerebral Blood Flow & Metabolism and European Journal of Nuclear Medicine and Molecular Imaging.

In The Last Decade

Sac-Pham Tang

8 papers receiving 350 citations

Author Peers

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

Author Last Decade Papers Cites
Sac-Pham Tang 127 122 81 78 51 9 357
Yvonne Lewis 155 1.2× 51 0.4× 66 0.8× 117 1.5× 52 1.0× 17 398
Emmanuelle Briard 114 0.9× 85 0.7× 71 0.9× 106 1.4× 113 2.2× 5 350
Yoshinori TERAMURA 208 1.6× 73 0.6× 57 0.7× 97 1.2× 21 0.4× 11 376
Tanja Obradovic 105 0.8× 145 1.2× 44 0.5× 102 1.3× 12 0.2× 8 362
Ian Gurrell 172 1.4× 53 0.4× 37 0.5× 47 0.6× 38 0.7× 14 394
Takayo Kida 148 1.2× 42 0.3× 35 0.4× 187 2.4× 93 1.8× 12 347
Dieter Ory 86 0.7× 32 0.3× 123 1.5× 33 0.4× 67 1.3× 7 309
Cyrille Thominiaux 142 1.1× 69 0.6× 91 1.1× 80 1.0× 124 2.4× 12 375
Éva Hellinger 92 0.7× 160 1.3× 142 1.8× 53 0.7× 7 0.1× 9 396
Padmashree S. Tirumalai 98 0.8× 40 0.3× 30 0.4× 67 0.9× 32 0.6× 8 349

Countries citing papers authored by Sac-Pham Tang

Since Specialization
Citations

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

Fields of papers citing papers by Sac-Pham Tang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sac-Pham Tang. 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 Sac-Pham Tang. The network helps show where Sac-Pham Tang may publish in the future.

Co-authorship network of co-authors of Sac-Pham Tang

This figure shows the co-authorship network connecting the top 25 collaborators of Sac-Pham Tang. A scholar is included among the top collaborators of Sac-Pham Tang 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 Sac-Pham Tang. Sac-Pham Tang 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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2026