Kang-Sik Park

1.2k total citations
24 papers, 915 citations indexed

About

Kang-Sik Park is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, Kang-Sik Park has authored 24 papers receiving a total of 915 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Molecular Biology, 8 papers in Cellular and Molecular Neuroscience and 7 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in Kang-Sik Park's work include Ion channel regulation and function (10 papers), Neuroscience and Neuropharmacology Research (8 papers) and Cardiac electrophysiology and arrhythmias (7 papers). Kang-Sik Park is often cited by papers focused on Ion channel regulation and function (10 papers), Neuroscience and Neuropharmacology Research (8 papers) and Cardiac electrophysiology and arrhythmias (7 papers). Kang-Sik Park collaborates with scholars based in South Korea, United States and France. Kang-Sik Park's co-authors include James S. Trimmer, Durga P. Mohapatra, Hiroaki Misonou, Jae‐Won Yang, Min‐Young Song, Yumi Kwon, Cheolju Lee, Milena Menegola, Sa Ik Bang and Sungho Shin and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Journal of Neuroscience.

In The Last Decade

Kang-Sik Park

23 papers receiving 908 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kang-Sik Park South Korea 15 635 335 202 108 89 24 915
Sumimasa Yamashita Japan 17 568 0.9× 231 0.7× 61 0.3× 98 0.9× 49 0.6× 53 994
Núria Comes Spain 22 853 1.3× 214 0.6× 324 1.6× 121 1.1× 24 0.3× 43 1.2k
Michaela Jaksch Germany 24 1.5k 2.3× 185 0.6× 122 0.6× 67 0.6× 41 0.5× 40 1.9k
Paola Lorenzon Italy 19 728 1.1× 284 0.8× 53 0.3× 151 1.4× 37 0.4× 62 1.2k
Rabary M. Rajerison France 20 732 1.2× 214 0.6× 72 0.4× 70 0.6× 121 1.4× 39 1.3k
Claus Hansen Denmark 17 621 1.0× 184 0.5× 73 0.4× 55 0.5× 21 0.2× 25 1.0k
Kim W. Chan United States 18 1.0k 1.6× 426 1.3× 346 1.7× 46 0.4× 12 0.1× 26 1.3k
Nanna K. Jørgensen Denmark 19 896 1.4× 328 1.0× 375 1.9× 142 1.3× 17 0.2× 26 1.1k
Vsevolod Telezhkin United Kingdom 15 359 0.6× 162 0.5× 78 0.4× 59 0.5× 35 0.4× 29 719
Bahman Aghdasi United States 9 786 1.2× 151 0.5× 258 1.3× 95 0.9× 22 0.2× 9 927

Countries citing papers authored by Kang-Sik Park

Since Specialization
Citations

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

Fields of papers citing papers by Kang-Sik Park

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kang-Sik Park

This figure shows the co-authorship network connecting the top 25 collaborators of Kang-Sik Park. A scholar is included among the top collaborators of Kang-Sik 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 Kang-Sik Park. Kang-Sik Park 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.
Ju, Shinyeong, Seonjeong Lee, So Ha Lee, et al.. (2025). Distinguishing N-Terminal Methylation from Near-Isobaric Modifications by Statistical Analysis of Mass Error Distributions of Fragment Ions. Journal of Proteome Research. 24(9). 4804–4815.
2.
Higerd‐Rusli, Grant P., Mohammad‐Reza Ghovanloo, Fadia B. Dib-Hajj, et al.. (2024). Compartment-specific regulation of NaV1.7 in sensory neurons after acute exposure to TNF-α. Cell Reports. 43(2). 113685–113685. 14 indexed citations
3.
Park, Na Rae, Yumi Kwon, Shinyeong Ju, et al.. (2023). One-STAGE Tip Method for TMT-Based Proteomic Analysis of a Minimal Amount of Cells. ACS Omega. 8(22). 19741–19751. 2 indexed citations
4.
Shin, Sungho, Jeongmin Lee, Yumi Kwon, et al.. (2021). Comparative Proteomic Analysis of the Mesenchymal Stem Cells Secretome from Adipose, Bone Marrow, Placenta and Wharton’s Jelly. International Journal of Molecular Sciences. 22(2). 845–845. 129 indexed citations
5.
Song, Min‐Young, Ji Yeon Hwang, Hye-Min Kang, et al.. (2020). Tyrosine Phosphorylation of the Kv2.1 Channel Contributes to Injury in Brain Ischemia. International Journal of Molecular Sciences. 21(24). 9538–9538. 2 indexed citations
6.
Kim, Dong‐Hyun, Kang-Sik Park, See‐Hyoung Park, Sang June Hahn, & Jin‐Sung Choi. (2020). Norquetiapine blocks the human cardiac sodium channel Nav1.5 in a state-dependent manner. European Journal of Pharmacology. 885. 173532–173532. 3 indexed citations
7.
Choi, Young Wook, Yang‐Gyun Kim, Min‐Young Song, et al.. (2017). Potential urine proteomics biomarkers for primary nephrotic syndrome. Clinical Proteomics. 14(1). 18–18. 32 indexed citations
8.
Song, Min‐Young, et al.. (2016). Global analysis of ginsenoside Rg1 protective effects in β-amyloid-treated neuronal cells. Journal of Ginseng Research. 41(4). 566–571. 21 indexed citations
9.
Hwang, Ji Yeon, et al.. (2015). Proteomic analysis reveals that the protective effects of ginsenoside Rb1 are associated with the actin cytoskeleton in β-amyloid-treated neuronal cells. Journal of Ginseng Research. 40(3). 278–284. 22 indexed citations
10.
Song, Min‐Young, et al.. (2014). Quantitative proteomic analysis reveals mitochondrial protein changes in MPP+-induced neuronal cells. Molecular BioSystems. 10(7). 1940–1947. 11 indexed citations
11.
Cerda, Oscar, Mónica Cáceres, Kang-Sik Park, et al.. (2014). Casein kinase-mediated phosphorylation of serine 839 is necessary for basolateral localization of the Ca2+-activated non-selective cation channel TRPM4. Pflügers Archiv - European Journal of Physiology. 467(8). 1723–1732. 12 indexed citations
12.
13.
Seo, Jung-Woo, et al.. (2013). Proteomic Analysis of Primary Cultured Rat Cortical Neurons in Chemical Ischemia. Neurochemical Research. 38(8). 1648–1660. 6 indexed citations
14.
Kim, Dong Hyun, et al.. (2013). Src regulates membrane trafficking of the Kv3.1b channel. FEBS Letters. 588(1). 86–91. 7 indexed citations
15.
16.
Song, Min‐Young, et al.. (2011). Identification of the phosphorylation sites on intact TRPM7 channels from mammalian cells. Biochemical and Biophysical Research Communications. 417(3). 1030–1034. 20 indexed citations
17.
Lee, Seung Eun, et al.. (2010). Differentially-expressed genes related to atherosclerosis in acrolein-stimulated human umbilical vein endothelial cells. BioChip Journal. 4(4). 264–271. 10 indexed citations
18.
Yang, Jae‐Won, Hélène Vacher, Kang-Sik Park, Eliana Clark, & James S. Trimmer. (2007). Trafficking-dependent phosphorylation of Kv1.2 regulates voltage-gated potassium channel cell surface expression. Proceedings of the National Academy of Sciences. 104(50). 20055–20060. 63 indexed citations
19.
Misonou, Hiroaki, et al.. (2006). Bidirectional Activity-Dependent Regulation of Neuronal Ion Channel Phosphorylation. Journal of Neuroscience. 26(52). 13505–13514. 91 indexed citations
20.
Park, Kang-Sik, Durga P. Mohapatra, Hiroaki Misonou, & James S. Trimmer. (2006). Graded Regulation of the Kv2.1 Potassium Channel by Variable Phosphorylation. Science. 313(5789). 976–979. 226 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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