Hui‐Yun Hwang

752 total citations · 1 hit paper
8 papers, 480 citations indexed

About

Hui‐Yun Hwang is a scholar working on Epidemiology, Physiology and Molecular Biology. According to data from OpenAlex, Hui‐Yun Hwang has authored 8 papers receiving a total of 480 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Epidemiology, 4 papers in Physiology and 3 papers in Molecular Biology. Recurrent topics in Hui‐Yun Hwang's work include Autophagy in Disease and Therapy (8 papers), Calcium signaling and nucleotide metabolism (4 papers) and Cannabis and Cannabinoid Research (2 papers). Hui‐Yun Hwang is often cited by papers focused on Autophagy in Disease and Therapy (8 papers), Calcium signaling and nucleotide metabolism (4 papers) and Cannabis and Cannabinoid Research (2 papers). Hui‐Yun Hwang collaborates with scholars based in South Korea, Sweden and Macao. Hui‐Yun Hwang's co-authors include Ho Jeong Kwon, Dasol Kim, Jong Shin Yoo, Jin Young Kim, Eun Sun Ji, Joong Sup Shim, H.J. Lim, Kihyoun Park, Haushabhau S. Pagire and Jinyoung Kim and has published in prestigious journals such as Nature Communications, Biochemical and Biophysical Research Communications and Autophagy.

In The Last Decade

Hui‐Yun Hwang

8 papers receiving 479 citations

Hit Papers

Activation of mitochondri... 2021 2026 2022 2024 2021 50 100 150

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Hui‐Yun Hwang South Korea 7 204 175 56 47 43 8 480
Stuart Gillies United Kingdom 8 255 1.3× 126 0.7× 51 0.9× 23 0.5× 32 0.7× 11 496
Xufeng Cen China 11 342 1.7× 198 1.1× 113 2.0× 80 1.7× 60 1.4× 22 691
Gerardo R. Corradi Argentina 12 225 1.1× 52 0.3× 63 1.1× 24 0.5× 55 1.3× 27 402
Sudeshna Dutta United States 5 356 1.7× 418 2.4× 53 0.9× 57 1.2× 125 2.9× 11 721
Adriana Covarrubias‐Pinto Germany 10 276 1.4× 256 1.5× 73 1.3× 33 0.7× 253 5.9× 17 643
Sabrina Schroeder Germany 7 305 1.5× 207 1.2× 63 1.1× 82 1.7× 80 1.9× 14 521
Izumi Kato Japan 8 261 1.3× 112 0.6× 84 1.5× 10 0.2× 52 1.2× 14 604
José Francisco Montiel-Sosa Mexico 8 311 1.5× 94 0.5× 97 1.7× 22 0.5× 17 0.4× 14 534
Lawrence J. Forsberg United States 11 409 2.0× 82 0.5× 40 0.7× 13 0.3× 56 1.3× 13 597
Sang‐Youel Park South Korea 14 246 1.2× 96 0.5× 45 0.8× 52 1.1× 30 0.7× 20 478

Countries citing papers authored by Hui‐Yun Hwang

Since Specialization
Citations

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

Fields of papers citing papers by Hui‐Yun Hwang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hui‐Yun Hwang. 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 Hui‐Yun Hwang. The network helps show where Hui‐Yun Hwang may publish in the future.

Co-authorship network of co-authors of Hui‐Yun Hwang

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

All Works

8 of 8 papers shown
1.
Kim, Dasol, Hui‐Yun Hwang, Eun Sun Ji, et al.. (2021). Activation of mitochondrial TUFM ameliorates metabolic dysregulation through coordinating autophagy induction. Communications Biology. 4(1). 1–1. 182 indexed citations breakdown →
2.
Kim, Dasol, Hui‐Yun Hwang, & Ho Jeong Kwon. (2021). A natural small molecule induces MAPT clearance via mTOR-independent autophagy. Biochemical and Biophysical Research Communications. 568. 30–36. 5 indexed citations
3.
Kim, Dasol, Hui‐Yun Hwang, & Ho Jeong Kwon. (2020). Targeting Autophagy In Disease: Recent Advances In Drug Discovery. Expert Opinion on Drug Discovery. 15(9). 1045–1063. 11 indexed citations
4.
Hwang, Hui‐Yun, Jin Young Kim, Ki Na Yun, et al.. (2020). Autophagic Inhibition via Lysosomal Integrity Dysfunction Leads to Antitumor Activity in Glioma Treatment. Cancers. 12(3). 543–543. 15 indexed citations
5.
Hwang, Hui‐Yun, Joong Sup Shim, Dasol Kim, & Ho Jeong Kwon. (2020). Antidepressant drug sertraline modulates AMPK-MTOR signaling-mediated autophagy via targeting mitochondrial VDAC1 protein. Autophagy. 17(10). 2783–2799. 84 indexed citations
6.
Lim, H.J., Kook Hwan Kim, Kihyoun Park, et al.. (2018). A novel autophagy enhancer as a therapeutic agent against metabolic syndrome and diabetes. Nature Communications. 9(1). 1438–1438. 125 indexed citations
7.
Hwang, Hui‐Yun, Sung Min Cho, & Ho Jeong Kwon. (2017). Approaches for discovering novel bioactive small molecules targeting autophagy. Expert Opinion on Drug Discovery. 12(9). 909–923. 10 indexed citations
8.
Hwang, Hui‐Yun, Jin Young Kim, Ju Yeon Lee, et al.. (2016). FK506, an Immunosuppressive Drug, Induces Autophagy by Binding to the V-ATPase Catalytic Subunit A in Neuronal Cells. Journal of Proteome Research. 16(1). 55–64. 48 indexed citations

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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