Sae-Hun Park

1.8k total citations · 1 hit paper
8 papers, 1.4k citations indexed

About

Sae-Hun Park is a scholar working on Molecular Biology, Cell Biology and Cellular and Molecular Neuroscience. According to data from OpenAlex, Sae-Hun Park has authored 8 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 5 papers in Cell Biology and 3 papers in Cellular and Molecular Neuroscience. Recurrent topics in Sae-Hun Park's work include Endoplasmic Reticulum Stress and Disease (5 papers), Genetic Neurodegenerative Diseases (3 papers) and RNA modifications and cancer (2 papers). Sae-Hun Park is often cited by papers focused on Endoplasmic Reticulum Stress and Disease (5 papers), Genetic Neurodegenerative Diseases (3 papers) and RNA modifications and cancer (2 papers). Sae-Hun Park collaborates with scholars based in Germany, United States and France. Sae-Hun Park's co-authors include F. Ulrich Hartl, Mark S. Hipp, Manajit Hayer‐Hartl, Dieter H. Wolf, Zlatka Kostova, Rajat Gupta, Ayano Konagai, Taotao Chen, Walter Neupert and Toshiaki Izawa and has published in prestigious journals such as Nature, Cell and Journal of Biological Chemistry.

In The Last Decade

Sae-Hun Park

6 papers receiving 1.4k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Proteostasis impairment in protein-misfolding and -aggregation diseases

2014 481 citations Mark S. Hipp, Sae-Hun Park et al. Trends in Cell Biology profile →

Peers

Sae-Hun Park

MB

CB

CMN

EPIDE

PHYSI

Rebecca Aron United States

Gopal Gunanathan Jayaraj India

Heidi Olzscha United Kingdom

Fernando Tomé Spain

Sergey S. Novoselov United Kingdom

Nava Zaarur United States

Courtney L. Klaips Germany

Vishwajeeth Pagala United States

Martin Borch Jensen United States

Lihong Zhao United States

Rebecca Aron United States

Sae-Hun Park

970 ×0.8

MB

404 ×0.6

CB

187 ×0.9

CMN

68 ×0.4

EPIDE

121 ×0.7

PHYSI

Citations per year, relative to Sae-Hun Park Sae-Hun Park (= 1×) peers Rebecca Aron

Countries citing papers authored by Sae-Hun Park

Since Specialization

Citations

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

Fields of papers citing papers by Sae-Hun Park

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sae-Hun Park. 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 Sae-Hun Park. The network helps show where Sae-Hun Park may publish in the future.

Co-authorship network of co-authors of Sae-Hun Park

This figure shows the co-authorship network connecting the top 25 collaborators of Sae-Hun Park. A scholar is included among the top collaborators of Sae-Hun Park 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 Sae-Hun Park. Sae-Hun Park is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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8 of 8 papers shown

1.

Izawa, Toshiaki, Serena Schwenkert, Stéphane Duvezin‐Caubet, et al.. (2025). Delayed protein translocation protects mitochondria against toxic CAT-tailed proteins. Molecular Cell. 85(21). 4082–4092.e7.

2.

Izawa, Toshiaki, Sae-Hun Park, Liang Zhao, F. Ulrich Hartl, & Walter Neupert. (2017). Cytosolic Protein Vms1 Links Ribosome Quality Control to Mitochondrial and Cellular Homeostasis. Cell. 171(4). 890–903.e18. 152 indexed citations

3.

Choe, Young‐Jun, Sae-Hun Park, Roman Körner, et al.. (2016). Failure of RQC machinery causes protein aggregation and proteotoxic stress. Nature. 531(7593). 191–195. 177 indexed citations

4.

Hipp, Mark S., Sae-Hun Park, & F. Ulrich Hartl. (2014). Proteostasis impairment in protein-misfolding and -aggregation diseases. Trends in Cell Biology. 24(9). 506–514. 481 indexed citations breakdown →

5.

Park, Sae-Hun, Rajat Gupta, Taotao Chen, et al.. (2013). PolyQ Proteins Interfere with Nuclear Degradation of Cytosolic Proteins by Sequestering the Sis1p Chaperone. Cell. 154(1). 134–145. 288 indexed citations

6.

Park, Sae-Hun, Frederik Eisele, Zlatka Kostova, et al.. (2006). The Cytoplasmic Hsp70 Chaperone Machinery Subjects Misfolded and Endoplasmic Reticulum Import-incompetent Proteins to Degradation via the Ubiquitin–Proteasome System. Molecular Biology of the Cell. 18(1). 153–165. 126 indexed citations

7.

Taxis, Christof, Reiner Hitt, Sae-Hun Park, et al.. (2003). Use of Modular Substrates Demonstrates Mechanistic Diversity and Reveals Differences in Chaperone Requirement of ERAD. Journal of Biological Chemistry. 278(38). 35903–35913. 156 indexed citations

8.

Jin, Ingnyol, et al.. (2002). Saccharomyces cerevisiae KNU5377 with multiple stress tolerance and its potential as a worldwide on-site industrial strain for alcohol fermentation. KRIBB Repository. 30(4). 425–429.

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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