Hye–Jun Shin

13 total papers · 522 total citations
10 papers, 436 citations indexed

About

Hye–Jun Shin is a scholar working on Molecular Biology, Epidemiology and Hepatology. According to data from OpenAlex, Hye–Jun Shin has authored 10 papers receiving a total of 436 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 6 papers in Epidemiology and 2 papers in Hepatology. Recurrent topics in Hye–Jun Shin's work include Hepatitis B Virus Studies (5 papers), Liver Disease Diagnosis and Treatment (4 papers) and Glutathione Transferases and Polymorphisms (2 papers). Hye–Jun Shin is often cited by papers focused on Hepatitis B Virus Studies (5 papers), Liver Disease Diagnosis and Treatment (4 papers) and Glutathione Transferases and Polymorphisms (2 papers). Hye–Jun Shin collaborates with scholars based in South Korea, United States and China. Hye–Jun Shin's co-authors include Dae‐Yeul Yu, Kook Hwan Kim, Hyeong Hoe Kim, JaeHun Cheong, Ung Suk Yang, Sang Hoon Rhee, Hyun Mi Choi, Kyeongjin Kim, Young‐Ho Park and Do‐Young Yoon and has published in prestigious journals such as Journal of Biological Chemistry, SHILAP Revista de lepidopterología and Gastroenterology.

In The Last Decade

Hye–Jun Shin

10 papers receiving 432 citations

Author Peers

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

Author Last Decade Papers Cites
Hye–Jun Shin 225 178 147 72 43 10 436
Hyeong Hoe Kim 260 1.2× 126 0.7× 171 1.2× 56 0.8× 82 1.9× 9 421
Yoshiyuki Sakamaki 289 1.3× 169 0.9× 115 0.8× 86 1.2× 64 1.5× 6 479
Su Suriguga 187 0.8× 151 0.8× 190 1.3× 39 0.5× 28 0.7× 13 445
Ezio David 245 1.1× 122 0.7× 288 2.0× 70 1.0× 45 1.0× 9 481
Natsuko Hada 298 1.3× 122 0.7× 126 0.9× 27 0.4× 33 0.8× 6 412
Marielena McGuire 173 0.8× 190 1.1× 69 0.5× 51 0.7× 32 0.7× 9 487
Il Hong 111 0.5× 163 0.9× 70 0.5× 56 0.8× 77 1.8× 9 419
Prachi Hote 231 1.0× 171 1.0× 60 0.4× 40 0.6× 29 0.7× 6 431
Michael Dudek 293 1.3× 176 1.0× 80 0.5× 44 0.6× 46 1.1× 11 482
Mark Lawson 210 0.9× 153 0.9× 119 0.8× 25 0.3× 41 1.0× 12 450

Countries citing papers authored by Hye–Jun Shin

Since Specialization
Citations

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

Fields of papers citing papers by Hye–Jun Shin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hye–Jun Shin. 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 Hye–Jun Shin. The network helps show where Hye–Jun Shin may publish in the future.

Co-authorship network of co-authors of Hye–Jun Shin

This figure shows the co-authorship network connecting the top 25 collaborators of Hye–Jun Shin. A scholar is included among the top collaborators of Hye–Jun Shin 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 Hye–Jun Shin. Hye–Jun Shin 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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