Daesung Shin

795 total citations
23 papers, 620 citations indexed

About

Daesung Shin is a scholar working on Molecular Biology, Physiology and Cell Biology. According to data from OpenAlex, Daesung Shin has authored 23 papers receiving a total of 620 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 10 papers in Physiology and 5 papers in Cell Biology. Recurrent topics in Daesung Shin's work include Lysosomal Storage Disorders Research (10 papers), Cellular transport and secretion (5 papers) and Neuroinflammation and Neurodegeneration Mechanisms (3 papers). Daesung Shin is often cited by papers focused on Lysosomal Storage Disorders Research (10 papers), Cellular transport and secretion (5 papers) and Neuroinflammation and Neurodegeneration Mechanisms (3 papers). Daesung Shin collaborates with scholars based in United States, South Korea and France. Daesung Shin's co-authors include Louis J. Ptáček, Ying‐Hui Fu, Michael T. McManus, Ji‐Yeon Shin, M. Laura Feltri, Lawrence Wrabetz, Chankyu Park, Yinghui Fu, Shuting Lin and Sang-Jin Park and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Nature Communications.

In The Last Decade

Daesung Shin

21 papers receiving 609 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daesung Shin United States 13 378 188 165 85 84 23 620
Karthikeyan Veeraraghavalu United States 9 233 0.6× 214 1.1× 49 0.3× 128 1.5× 57 0.7× 10 572
Illar Pata Estonia 12 464 1.2× 86 0.5× 85 0.5× 40 0.5× 40 0.5× 21 703
Ikuri Álvarez-Maya Mexico 8 452 1.2× 52 0.3× 99 0.6× 182 2.1× 58 0.7× 17 756
Siew Ping Han Australia 13 614 1.6× 78 0.4× 89 0.5× 23 0.3× 255 3.0× 14 949
Yuan Xie United States 13 529 1.4× 39 0.2× 82 0.5× 78 0.9× 96 1.1× 19 723
Marco Henneke Germany 19 834 2.2× 80 0.4× 59 0.4× 38 0.4× 120 1.4× 35 1.1k
Gabriel Balmus United Kingdom 15 477 1.3× 70 0.4× 64 0.4× 22 0.3× 46 0.5× 26 784
Tomohiko Iwano Japan 15 539 1.4× 157 0.8× 49 0.3× 117 1.4× 212 2.5× 27 962
Guangming Gan China 13 518 1.4× 41 0.2× 305 1.8× 28 0.3× 79 0.9× 28 829

Countries citing papers authored by Daesung Shin

Since Specialization
Citations

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

Fields of papers citing papers by Daesung Shin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daesung Shin

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

All Works

20 of 20 papers shown
1.
Patel, Mayuri, et al.. (2024). Perinatal loss of galactosylceramidase in both oligodendrocytes and microglia is crucial for the pathogenesis of Krabbe disease in mice. Molecular Therapy. 32(7). 2207–2222. 3 indexed citations
2.
Thompson, David C., et al.. (2024). Ablation of lipocalin-2 reduces neuroinflammation in a mouse model of Krabbe disease. Scientific Reports. 14(1). 31822–31822.
3.
Hong, Xinying, et al.. (2022). Neuron-specific ablation of the Krabbe disease gene galactosylceramidase in mice results in neurodegeneration. PLoS Biology. 20(7). e3001661–e3001661. 12 indexed citations
4.
Feltri, M. Laura, et al.. (2021). Mechanisms of demyelination and neurodegeneration in globoid cell leukodystrophy. Glia. 69(10). 2309–2331. 29 indexed citations
5.
Nguyen, Duc, et al.. (2020). Brainstem development requires galactosylceramidase and is critical for pathogenesis in a model of Krabbe disease. Nature Communications. 11(1). 5356–5356. 29 indexed citations
6.
Shin, Daesung, Xinying Hong, Eric E. Irons, et al.. (2020). Macrophages Expressing GALC Improve Peripheral Krabbe Disease by a Mechanism Independent of Cross-Correction. Neuron. 107(1). 65–81.e9. 44 indexed citations
7.
Feltri, M. Laura, et al.. (2020). Pre-clinical Mouse Models of Neurodegenerative Lysosomal Storage Diseases. Frontiers in Molecular Biosciences. 7. 57–57. 20 indexed citations
8.
Shin, Daesung, et al.. (2018). A Study on the Standardization Model of Entrepreneurship Support Using ICT Convergence. 8(1). 13–22. 3 indexed citations
9.
Shin, Daesung, et al.. (2018). Temporal Galc deletion reveals a critical vulnerable period in the pathogenesis of Krabbe leukodystrophy. Molecular Genetics and Metabolism. 123(2). S131–S131. 1 indexed citations
10.
Shin, Daesung, M. Laura Feltri, & Lawrence Wrabetz. (2016). Altered Trafficking and Processing ofGALCMutants Correlates with Globoid Cell Leukodystrophy Severity. Journal of Neuroscience. 36(6). 1858–1870. 32 indexed citations
11.
Wrabetz, Lawrence, et al.. (2016). Metabolic profiling reveals biochemical pathways and potential biomarkers associated with the pathogenesis ofKrabbe disease. Journal of Neuroscience Research. 94(11). 1094–1107. 10 indexed citations
12.
Shin, Daesung, Shuting Lin, Yinghui Fu, & Louis J. Ptáček. (2013). Very large G protein-coupled receptor 1 regulates myelin-associated glycoprotein via Gαs/Gαq-mediated protein kinases A/C. Proceedings of the National Academy of Sciences. 110(47). 19101–19106. 46 indexed citations
13.
Shin, Daesung, et al.. (2012). miR-32 and its target SLC45A3 regulate the lipid metabolism of oligodendrocytes and myelin. Neuroscience. 213. 29–37. 52 indexed citations
14.
Shao, Yan, Sang Yong Kim, Daesung Shin, et al.. (2010). TXNIP regulates germinal center generation by suppressing BCL-6 expression. Immunology Letters. 129(2). 78–84. 12 indexed citations
15.
Shin, Daesung, Ji‐Yeon Shin, Michael T. McManus, Louis J. Ptáček, & Ying‐Hui Fu. (2009). Dicer ablation in oligodendrocytes provokes neuronal impairment in mice. Annals of Neurology. 66(6). 843–857. 170 indexed citations
16.
Lee, Chaeyoung, Changhoon Kim, Sooan Shin, et al.. (2008). The dopamine D4 receptor polymorphism affects the canine fearfulness. Animal Cells and Systems. 12(2). 77–83. 5 indexed citations
17.
Shin, Daesung, Mira Jeong, Hyun‐Woo Suh, et al.. (2007). VDUP1 mediates nuclear export of HIF1α via CRM1-dependent pathway. Biochimica et Biophysica Acta (BBA) - Molecular Cell Research. 1783(5). 838–848. 61 indexed citations
18.
Shin, Daesung & Chankyu Park. (2004). N-terminal Extension of Canine Glutamine Synthetase Created by Splicing Alters Its Enzymatic Property. Journal of Biological Chemistry. 279(2). 1184–1190. 15 indexed citations
19.
Werner, Petra, M Raducha, Daesung Shin, et al.. (2004). Assignment of 10 canine genes to the canine linkage and comparative maps. Animal Genetics. 35(3). 249–251. 3 indexed citations
20.
Kim, In‐Sook, et al.. (2004). Ribose Utilization with an Excess of Mutarotase Causes Cell Death Due to Accumulation of Methylglyoxal. Journal of Bacteriology. 186(21). 7229–7235. 27 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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