Tai C. Chen

436 total papers · 28.4k total citations
304 papers, 21.0k citations indexed

About

Tai C. Chen is a scholar working on Pathology and Forensic Medicine, Molecular Biology and Genetics. According to data from OpenAlex, Tai C. Chen has authored 304 papers receiving a total of 21.0k indexed citations (citations by other indexed papers that have themselves been cited), including 140 papers in Pathology and Forensic Medicine, 61 papers in Molecular Biology and 52 papers in Genetics. Recurrent topics in Tai C. Chen's work include Vitamin D Research Studies (132 papers), Estrogen and related hormone effects (38 papers) and Vitamin C and Antioxidants Research (19 papers). Tai C. Chen is often cited by papers focused on Vitamin D Research Studies (132 papers), Estrogen and related hormone effects (38 papers) and Vitamin C and Antioxidants Research (19 papers). Tai C. Chen collaborates with scholars based in United States, Japan and Taiwan. Tai C. Chen's co-authors include Michael F. Holick, Jacobo Wortsman, Lois Y. Matsuoka, Z. Lu, Robert P. Heaney, M. Janet Barger-Lux, Vin Tangpricha, K. Michael Davies, Adrian K. Turner and Zhiren Lu and has published in prestigious journals such as Science, New England Journal of Medicine and Proceedings of the National Academy of Sciences.

In The Last Decade

Tai C. Chen

297 papers receiving 20.0k citations

Hit Papers

Decreased bioavailability... 2000 2026 2008 2017 2000 2008 2003 2007 500 1000 1.5k 2.0k

Author Peers

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

Author Last Decade Papers Cites
Tai C. Chen 13.0k 5.0k 3.3k 3.1k 2.5k 304 21.0k
Stefan Pilz 8.3k 0.6× 4.0k 0.8× 2.2k 0.7× 1.9k 0.6× 1.5k 0.6× 368 17.0k
Connie M. Weaver 10.5k 0.8× 7.0k 1.4× 5.8k 1.8× 5.4k 1.7× 3.3k 1.3× 478 26.0k
Bruce W. Hollis 21.5k 1.7× 7.8k 1.6× 6.1k 1.8× 5.1k 1.7× 2.4k 1.0× 340 29.6k
Steven A. Abrams 5.7k 0.4× 8.8k 1.8× 3.5k 1.1× 3.3k 1.1× 1.4k 0.6× 366 19.8k
David A. Hanley 9.5k 0.7× 3.6k 0.7× 7.9k 2.4× 2.3k 0.8× 2.4k 1.0× 197 18.5k
John S. Adams 8.6k 0.7× 3.4k 0.7× 1.9k 0.6× 1.2k 0.4× 2.3k 0.9× 210 14.7k
Daniel D. Bikle 11.1k 0.9× 4.0k 0.8× 3.5k 1.1× 1.3k 0.4× 7.0k 2.9× 359 24.9k
William B. Grant 9.9k 0.8× 4.8k 1.0× 1.9k 0.6× 2.4k 0.8× 801 0.3× 317 17.2k
Neil Binkley 13.2k 1.0× 5.7k 1.1× 12.8k 3.9× 2.8k 0.9× 3.7k 1.5× 384 29.4k
Munro Peacock 4.7k 0.4× 2.5k 0.5× 6.7k 2.0× 1.4k 0.4× 3.6k 1.5× 289 18.5k

Countries citing papers authored by Tai C. Chen

Since Specialization
Citations

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

Fields of papers citing papers by Tai C. Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tai C. Chen. 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 Tai C. Chen. The network helps show where Tai C. Chen may publish in the future.

Co-authorship network of co-authors of Tai C. Chen

This figure shows the co-authorship network connecting the top 25 collaborators of Tai C. Chen. A scholar is included among the top collaborators of Tai C. Chen 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 Tai C. Chen. Tai C. Chen 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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