Suk‐Jo Kang

2.4k total citations
44 papers, 1.9k citations indexed

About

Suk‐Jo Kang is a scholar working on Immunology, Molecular Biology and Oncology. According to data from OpenAlex, Suk‐Jo Kang has authored 44 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Immunology, 14 papers in Molecular Biology and 6 papers in Oncology. Recurrent topics in Suk‐Jo Kang's work include Immune Response and Inflammation (14 papers), Immune Cell Function and Interaction (13 papers) and T-cell and B-cell Immunology (10 papers). Suk‐Jo Kang is often cited by papers focused on Immune Response and Inflammation (14 papers), Immune Cell Function and Interaction (13 papers) and T-cell and B-cell Immunology (10 papers). Suk‐Jo Kang collaborates with scholars based in South Korea, United States and United Kingdom. Suk‐Jo Kang's co-authors include Peter Cresswell, Richard M. Locksley, Hong-Erh Liang, Minhyeok Kim, Boris Reizis, YoungJu Jo, YongKeun Park, R. Lee Reinhardt, Weiming Yuan and Bong Geun and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Journal of Biological Chemistry.

In The Last Decade

Suk‐Jo Kang

42 papers receiving 1.8k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Suk‐Jo Kang South Korea 22 1.1k 468 229 220 179 44 1.9k
Aki Manninen Finland 28 628 0.6× 1.2k 2.5× 214 0.9× 100 0.5× 134 0.7× 66 2.2k
Sandrine Lécart France 17 578 0.5× 314 0.7× 112 0.5× 169 0.8× 88 0.5× 26 1.5k
Ed Luther United States 19 727 0.7× 961 2.1× 537 2.3× 216 1.0× 35 0.2× 37 2.2k
Ann P. Wheeler United Kingdom 21 1.2k 1.1× 1.7k 3.7× 447 2.0× 146 0.7× 42 0.2× 36 3.1k
Renaud Poincloux France 29 645 0.6× 1.2k 2.5× 504 2.2× 457 2.1× 163 0.9× 50 3.4k
Dominic Waithe United Kingdom 27 318 0.3× 1.0k 2.2× 72 0.3× 220 1.0× 211 1.2× 49 2.0k
Susan K. Pierce United States 27 1.6k 1.5× 514 1.1× 186 0.8× 36 0.2× 41 0.2× 47 2.4k
Debasish Sen United States 15 614 0.6× 344 0.7× 173 0.8× 252 1.1× 19 0.1× 23 1.3k
Kenta Terai Japan 24 789 0.7× 1.6k 3.3× 492 2.1× 107 0.5× 25 0.1× 66 2.9k
Navin Varadarajan United States 24 598 0.5× 832 1.8× 483 2.1× 353 1.6× 16 0.1× 62 1.8k

Countries citing papers authored by Suk‐Jo Kang

Since Specialization
Citations

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

Fields of papers citing papers by Suk‐Jo Kang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Suk‐Jo Kang. 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 Suk‐Jo Kang. The network helps show where Suk‐Jo Kang may publish in the future.

Co-authorship network of co-authors of Suk‐Jo Kang

This figure shows the co-authorship network connecting the top 25 collaborators of Suk‐Jo Kang. A scholar is included among the top collaborators of Suk‐Jo Kang 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 Suk‐Jo Kang. Suk‐Jo Kang 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.
Park, Sunghyouk, et al.. (2025). Cancer-intrinsic Cxcl5 orchestrates a global metabolic reprogramming for resistance to oxidative cell death in 3D. Cell Death and Differentiation. 32(7). 1200–1213. 1 indexed citations
2.
Park, Jiyeon & Suk‐Jo Kang. (2024). The ontogenesis and heterogeneity of basophils. PubMed. 3(1). kyae003–kyae003. 4 indexed citations
3.
4.
Kang, Suk‐Jo, et al.. (2023). MARCH5 promotes STING pathway activation by suppressing polymer formation of oxidized STING. EMBO Reports. 24(12). e57496–e57496. 6 indexed citations
5.
Choi, Baekgyu, Chang Kyung Kang, Seong-Wan Park, et al.. (2022). Single-cell transcriptome analyses reveal distinct gene expression signatures of severe COVID-19 in the presence of clonal hematopoiesis. Experimental & Molecular Medicine. 54(10). 1756–1765. 5 indexed citations
6.
Park, Jiyeon, Seung Woo Choi, Bong Geun, Jaeyun Kim, & Suk‐Jo Kang. (2021). Alternative Activation of Macrophages through Interleukin-13-Loaded Extra-Large-Pore Mesoporous Silica Nanoparticles Suppresses Experimental Autoimmune Encephalomyelitis. ACS Biomaterials Science & Engineering. 7(9). 4446–4453. 11 indexed citations
7.
Yang, Dongchan, Mirang Kim, Jae‐Hoon Choi, et al.. (2018). Inflammation induces two types of inflammatory dendritic cells in inflamed lymph nodes. Experimental & Molecular Medicine. 50(3). e458–e458. 49 indexed citations
8.
Jo, YoungJu, Sang-Jin Park, JaeHwang Jung, et al.. (2017). Holographic deep learning for rapid optical screening of anthrax spores. Science Advances. 3(8). e1700606–e1700606. 130 indexed citations
9.
Sesaki, Hiromi, et al.. (2017). Carbonyl cyanide 3-chlorophenylhydrazone (CCCP) suppresses STING-mediated DNA sensing pathway through inducing mitochondrial fission. Biochemical and Biophysical Research Communications. 493(1). 737–743. 35 indexed citations
10.
Seo, Hyungseok, Insu Jeon, Byung‐Seok Kim, et al.. (2017). IL-21-mediated reversal of NK cell exhaustion facilitates anti-tumour immunity in MHC class I-deficient tumours. Nature Communications. 8(1). 15776–15776. 135 indexed citations
11.
Kim, Minhyeok, Dongchan Yang, Mirang Kim, et al.. (2017). A late-lineage murine neutrophil precursor population exhibits dynamic changes during demand-adapted granulopoiesis. Scientific Reports. 7(1). 39804–39804. 54 indexed citations
12.
Yoon, Jonghee, YoungJu Jo, Minhyeok Kim, et al.. (2017). Identification of non-activated lymphocytes using three-dimensional refractive index tomography and machine learning. Scientific Reports. 7(1). 6654–6654. 91 indexed citations
13.
Lee, Mi‐Kyung, Jang Hyun Lee, Kyung‐Eun Lim, et al.. (2016). Structural features of influenza A virus panhandle RNA enabling the activation of RIG-I independently of 5′-triphosphate. Nucleic Acids Research. 44(17). 8407–8416. 25 indexed citations
14.
Kang, Suk‐Jo. (2012). The Bloodline of CD8α+ Dendritic Cells. Molecules and Cells. 34(3). 219–230. 4 indexed citations
15.
Yuan, Weiming, Suk‐Jo Kang, James Evans, & Peter Cresswell. (2009). Natural Lipid Ligands Associated with Human CD1d Targeted to Different Subcellular Compartments. The Journal of Immunology. 182(8). 4784–4791. 75 indexed citations
16.
Kang, Suk‐Jo & Richard M. Locksley. (2009). The inflammasome and alum-mediated adjuvanticity. F1000 Biology Reports. 1. 15–15. 10 indexed citations
17.
Kang, Suk‐Jo, Hong-Erh Liang, Boris Reizis, & Richard M. Locksley. (2008). Regulation of Hierarchical Clustering and Activation of Innate Immune Cells by Dendritic Cells. Immunity. 29(5). 819–833. 142 indexed citations
18.
Yuan, Weiming, Xiaoyang Qi, Suk‐Jo Kang, et al.. (2007). Saposin B is the dominant saposin that facilitates lipid binding to human CD1d molecules. Proceedings of the National Academy of Sciences. 104(13). 5551–5556. 91 indexed citations
19.
Reinhardt, R. Lee, Suk‐Jo Kang, Hong-Erh Liang, & Richard M. Locksley. (2006). T helper cell effector fates — who, how and where?. Current Opinion in Immunology. 18(3). 271–277. 55 indexed citations
20.
Kang, Suk‐Jo & Peter Cresswell. (2004). Saposins facilitate CD1d-restricted presentation of an exogenous lipid antigen to T cells. Nature Immunology. 5(2). 175–181. 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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