Tse‐Hua Tan

190 total papers · 13.2k total citations
150 papers, 11.3k citations indexed

About

Tse‐Hua Tan is a scholar working on Molecular Biology, Immunology and Oncology. According to data from OpenAlex, Tse‐Hua Tan has authored 150 papers receiving a total of 11.3k indexed citations (citations by other indexed papers that have themselves been cited), including 100 papers in Molecular Biology, 63 papers in Immunology and 37 papers in Oncology. Recurrent topics in Tse‐Hua Tan's work include NF-κB Signaling Pathways (33 papers), Melanoma and MAPK Pathways (26 papers) and Cytokine Signaling Pathways and Interactions (23 papers). Tse‐Hua Tan is often cited by papers focused on NF-κB Signaling Pathways (33 papers), Melanoma and MAPK Pathways (26 papers) and Cytokine Signaling Pathways and Interactions (23 papers). Tse‐Hua Tan collaborates with scholars based in United States, Taiwan and Germany. Tse‐Hua Tan's co-authors include Yi‐Rong Chen, Christian F. Meyer, Daniel Eliyahu, Philip W. Hinds, Arnold J. Levine, Cathy A. Finlay, Moshe Oren, Dennis J. Templeton, Rong Yu and Guisheng Zhou and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Nucleic Acids Research.

In The Last Decade

Tse‐Hua Tan

148 papers receiving 11.0k citations

Hit Papers

Activating mutations for ... 1988 2026 2000 2013 1988 1996 250 500 750 1000

Author Peers

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

Author Last Decade Papers Cites
Tse‐Hua Tan 7.3k 3.1k 2.9k 2.1k 960 150 11.3k
Dan A. Liebermann 7.4k 1.0× 3.9k 1.3× 2.0k 0.7× 1.8k 0.8× 745 0.8× 138 11.1k
Andreas Villunger 7.5k 1.0× 3.1k 1.0× 2.8k 1.0× 1.4k 0.7× 1.2k 1.2× 183 10.6k
Gail E. Sonenshein 6.7k 0.9× 2.8k 0.9× 2.3k 0.8× 3.3k 1.6× 661 0.7× 155 10.9k
Trevor D. Littlewood 8.5k 1.2× 3.4k 1.1× 2.0k 0.7× 1.6k 0.7× 982 1.0× 78 11.7k
Roberta Buono 7.5k 1.0× 2.1k 0.7× 3.3k 1.1× 1.3k 0.6× 767 0.8× 128 11.5k
Surender Kharbanda 12.1k 1.7× 4.0k 1.3× 2.2k 0.8× 2.1k 1.0× 1.4k 1.5× 190 15.5k
F Grignani 10.2k 1.4× 2.2k 0.7× 3.0k 1.0× 1.8k 0.9× 778 0.8× 172 14.8k
Lawrence M. Pfeffer 5.4k 0.7× 3.2k 1.0× 3.6k 1.2× 3.1k 1.4× 475 0.5× 193 10.7k
Maryla Krajewska 8.1k 1.1× 3.7k 1.2× 2.0k 0.7× 2.1k 1.0× 941 1.0× 103 12.6k
Paul J. Chiao 7.1k 1.0× 3.7k 1.2× 2.0k 0.7× 4.0k 1.9× 657 0.7× 135 11.1k

Countries citing papers authored by Tse‐Hua Tan

Since Specialization
Citations

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

Fields of papers citing papers by Tse‐Hua Tan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tse‐Hua Tan. 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 Tse‐Hua Tan. The network helps show where Tse‐Hua Tan may publish in the future.

Co-authorship network of co-authors of Tse‐Hua Tan

This figure shows the co-authorship network connecting the top 25 collaborators of Tse‐Hua Tan. A scholar is included among the top collaborators of Tse‐Hua Tan 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 Tse‐Hua Tan. Tse‐Hua Tan 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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