Taehoon G. Lee

27 total papers · 2.0k total citations
25 papers, 1.7k citations indexed

About

Taehoon G. Lee is a scholar working on Molecular Biology, Cell Biology and Endocrinology, Diabetes and Metabolism. According to data from OpenAlex, Taehoon G. Lee has authored 25 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Molecular Biology, 4 papers in Cell Biology and 3 papers in Endocrinology, Diabetes and Metabolism. Recurrent topics in Taehoon G. Lee's work include Metabolism, Diabetes, and Cancer (7 papers), Protein Kinase Regulation and GTPase Signaling (6 papers) and S100 Proteins and Annexins (3 papers). Taehoon G. Lee is often cited by papers focused on Metabolism, Diabetes, and Cancer (7 papers), Protein Kinase Regulation and GTPase Signaling (6 papers) and S100 Proteins and Annexins (3 papers). Taehoon G. Lee collaborates with scholars based in South Korea, United States and Japan. Taehoon G. Lee's co-authors include Sung Ho Ryu, Yoe‐Sik Bae, Pann‐Ghill Suh, Jae Ho Kim, Hee‐Sup Shin, Stephen M. Smith, Richard W. Tsien, Michael E. Adams, Richard H. Scheller and David B. Wheeler and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Blood.

In The Last Decade

Taehoon G. Lee

25 papers receiving 1.7k citations

Author Peers

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

Author Last Decade Papers Cites
Taehoon G. Lee 1.0k 381 226 216 208 25 1.7k
Gabriele Stumm 632 0.6× 349 0.9× 257 1.1× 168 0.8× 195 0.9× 23 1.6k
Hua Yu 887 0.9× 358 0.9× 209 0.9× 187 0.9× 122 0.6× 42 1.6k
Carolanne E. Milligan 1.0k 1.0× 541 1.4× 263 1.2× 171 0.8× 206 1.0× 28 1.8k
Daniel Palmer 1.4k 1.4× 342 0.9× 358 1.6× 169 0.8× 306 1.5× 27 2.1k
Sylvie Cazaubon 1.2k 1.1× 261 0.7× 298 1.3× 303 1.4× 296 1.4× 35 2.3k
Murat Digicaylioglu 767 0.7× 315 0.8× 228 1.0× 210 1.0× 86 0.4× 28 1.9k
Maged M. Harraz 1.0k 1.0× 214 0.6× 232 1.0× 141 0.7× 274 1.3× 31 1.9k
Tatyana Merkulova‐Rainon 1.3k 1.2× 302 0.8× 161 0.7× 130 0.6× 115 0.6× 42 1.9k
Nicholas E. Hoffman 1.5k 1.5× 227 0.6× 300 1.3× 149 0.7× 178 0.9× 27 2.2k
Carole L. Jelsema 1.1k 1.1× 364 1.0× 215 1.0× 230 1.1× 259 1.2× 25 1.7k

Countries citing papers authored by Taehoon G. Lee

Since Specialization
Citations

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

Fields of papers citing papers by Taehoon G. Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Taehoon G. Lee. 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 Taehoon G. Lee. The network helps show where Taehoon G. Lee may publish in the future.

Co-authorship network of co-authors of Taehoon G. Lee

This figure shows the co-authorship network connecting the top 25 collaborators of Taehoon G. Lee. A scholar is included among the top collaborators of Taehoon G. Lee 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 Taehoon G. Lee. Taehoon G. Lee 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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