Yoon‐Seong Kim

1.3k total citations
28 papers, 1.0k citations indexed

About

Yoon‐Seong Kim is a scholar working on Neurology, Molecular Biology and Cellular and Molecular Neuroscience. According to data from OpenAlex, Yoon‐Seong Kim has authored 28 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Neurology, 12 papers in Molecular Biology and 11 papers in Cellular and Molecular Neuroscience. Recurrent topics in Yoon‐Seong Kim's work include Parkinson's Disease Mechanisms and Treatments (13 papers), Nuclear Receptors and Signaling (7 papers) and RNA regulation and disease (4 papers). Yoon‐Seong Kim is often cited by papers focused on Parkinson's Disease Mechanisms and Treatments (13 papers), Nuclear Receptors and Signaling (7 papers) and RNA regulation and disease (4 papers). Yoon‐Seong Kim collaborates with scholars based in United States, South Korea and Portugal. Yoon‐Seong Kim's co-authors include Goun Je, Subhrangshu Guhathakurta, Eugene Bok, Ana Clara Cristóvão, Dong‐Hee Choi, Soo‐Youl Kim, Tai Ryoon Han, Tong H. Joh, Jong Min Lee and Moon Suk Bang and has published in prestigious journals such as Journal of Biological Chemistry, Nature Communications and Journal of Neuroscience.

In The Last Decade

Yoon‐Seong Kim

28 papers receiving 1.0k citations

Peers

Yoon‐Seong Kim

NEURO

CMN

PRM

PHYSI

Minee L. Choi United Kingdom

Honglin Feng China

Phillip M. Rappold United States

Nirit Lev Israel

Chengyuan Mao China

Alexey V. Berezhnov Russia

Serenella Anzilotti Italy

Sarah Mustafa United Kingdom

Bao Wang China

Mary K. Herrick United States

Minee L. Choi United Kingdom

Yoon‐Seong Kim

380 ×1.0

349 ×1.0

NEURO

205 ×0.7

CMN

102 ×0.6

PRM

356 ×2.4

PHYSI

Citations per year, relative to Yoon‐Seong Kim Yoon‐Seong Kim (= 1×) peers Minee L. Choi

Countries citing papers authored by Yoon‐Seong Kim

Since Specialization

Citations

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

Fields of papers citing papers by Yoon‐Seong Kim

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yoon‐Seong Kim. 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 Yoon‐Seong Kim. The network helps show where Yoon‐Seong Kim may publish in the future.

Co-authorship network of co-authors of Yoon‐Seong Kim

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

All Works

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20 of 20 papers shown

Diogo, João C. F., et al.. (2024). NADPH Oxidases in Neurodegenerative Disorders: Mechanisms and Therapeutic Opportunities. Antioxidants and Redox Signaling. 41(7-9). 522–541. 8 indexed citations

Song, Min Kyung, et al.. (2024). A single-nuclei paired multiomic analysis of the human midbrain reveals age- and Parkinson’s disease–associated glial changes. Nature Aging. 4(3). 364–378. 14 indexed citations

Kim, Woori, Mohit Tripathi, Chun‐Hyung Kim, et al.. (2023). An optimized Nurr1 agonist provides disease-modifying effects in Parkinson’s disease models. Nature Communications. 14(1). 4283–4283. 26 indexed citations

Song, Minkyung, Goun Je, Subhrangshu Guhathakurta, et al.. (2023). Transcriptional mutagenesis of α-synuclein caused by DNA oxidation in Parkinson’s disease pathogenesis. Acta Neuropathologica. 146(5). 685–705. 10 indexed citations

Kim, Yoon‐Seong, et al.. (2022). Validation of analytical methods for acrylic acid from various food products. Food Science and Biotechnology. 31(11). 1377–1387. 1 indexed citations

Song, Min Kyung, et al.. (2022). NXP031 prevents dopaminergic neuronal loss and oxidative damage in the AAV-WT-α-synuclein mouse model of Parkinson’s disease. PLoS ONE. 17(7). e0272085–e0272085. 7 indexed citations

Guhathakurta, Subhrangshu, et al.. (2022). Regulation of Αlpha-Synuclein Gene (SNCA) by Epigenetic Modifier TET1 in Parkinson Disease. International Neurourology Journal. 26(Suppl 2). S85–93. 6 indexed citations

Guhathakurta, Subhrangshu, et al.. (2021). Targeted attenuation of elevated histone marks at SNCA alleviates α‐synuclein in Parkinson's disease. EMBO Molecular Medicine. 13(2). e12188–e12188. 65 indexed citations

Cristóvão, Ana Clara, Filipa L. Campos, Goun Je, et al.. (2020). Characterization of a Parkinson’s disease rat model using an upgraded paraquat exposure paradigm. European Journal of Neuroscience. 52(4). 3242–3255. 20 indexed citations

10.

Kim, Yoon‐Seong, et al.. (2018). FaptaSyme: A Strategy for Converting a Monomer/Oligomer‐Nonselective Aptameric Sensor into an Oligomer‐Selective One. ChemBioChem. 19(11). 1123–1126. 4 indexed citations

11.

Guhathakurta, Subhrangshu, et al.. (2017). Deregulation of α-synuclein in Parkinson’s disease: Insight from epigenetic structure and transcriptional regulation of SNCA. Progress in Neurobiology. 154. 21–36. 57 indexed citations

12.

Guhathakurta, Subhrangshu, et al.. (2017). Hypomethylation of intron1 of α-synuclein gene does not correlate with Parkinson’s disease. Molecular Brain. 10(1). 6–6. 38 indexed citations

13.

Je, Goun & Yoon‐Seong Kim. (2017). Mitochondrial ROS-mediated post-transcriptional regulation of α-synuclein through miR-7 and miR-153. Neuroscience Letters. 661. 132–136. 44 indexed citations

14.

Je, Goun, et al.. (2015). Transcriptional mutagenesis by 8-oxodG in α-synuclein aggregation and the pathogenesis of Parkinson’s disease. Experimental & Molecular Medicine. 47(8). e179–e179. 30 indexed citations

15.

Campos, Filipa L., Miguel M. Carvalho, Ana Clara Cristóvão, et al.. (2013). Rodent models of Parkinson's disease: beyond the motor symptomatology. Frontiers in Behavioral Neuroscience. 7. 175–175. 144 indexed citations

16.

Kim, Jisoo, et al.. (2013). Tnfaip8l1/Oxi-β binds to FBXW5, increasing autophagy through activation of TSC2 in a Parkinson's disease model. Journal of Neurochemistry. n/a–n/a. 4 indexed citations

17.

Lee, Kang‐Woo, Joo‐Young Im, Jongmin Jacob Woo, et al.. (2013). Neuroprotective and Anti-inflammatory Properties of a Coffee Component in the MPTP Model of Parkinson's Disease. Neurotherapeutics. 10(1). 143–153. 59 indexed citations

18.

Cristóvão, Ana Clara, Subhrangshu Guhathakurta, Eugene Bok, et al.. (2012). NADPH Oxidase 1 Mediates α-Synucleinopathy in Parkinson's Disease. Journal of Neuroscience. 32(42). 14465–14477. 80 indexed citations

19.

Choi, Dong‐Hee, Onyou Hwang, Kyoung‐Hee Lee, et al.. (2010). DJ-1 Cleavage by Matrix Metalloproteinase 3 Mediates Oxidative Stress-Induced Dopaminergic Cell Death. Antioxidants and Redox Signaling. 14(11). 2137–2150. 26 indexed citations

20.

Lee, Jong Min, Yoon‐Seong Kim, Dong‐Hee Choi, et al.. (2004). Transglutaminase 2 Induces Nuclear Factor-κB Activation via a Novel Pathway in BV-2 Microglia. Journal of Biological Chemistry. 279(51). 53725–53735. 170 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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