Ki Sa Sung

1.0k total citations
18 papers, 606 citations indexed

About

Ki Sa Sung is a scholar working on Molecular Biology, Oncology and Epidemiology. According to data from OpenAlex, Ki Sa Sung has authored 18 papers receiving a total of 606 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Molecular Biology, 11 papers in Oncology and 3 papers in Epidemiology. Recurrent topics in Ki Sa Sung's work include Ubiquitin and proteasome pathways (12 papers), Cancer-related Molecular Pathways (8 papers) and Autophagy in Disease and Therapy (3 papers). Ki Sa Sung is often cited by papers focused on Ubiquitin and proteasome pathways (12 papers), Cancer-related Molecular Pathways (8 papers) and Autophagy in Disease and Therapy (3 papers). Ki Sa Sung collaborates with scholars based in South Korea, United States and Israel. Ki Sa Sung's co-authors include Cheol Yong Choi, Yong Tae Kwon, Eun‐A Kim, Dong Wook Choi, Nathan A. Ellis, Shanshan Zhu, Jianmei Zhu, Michael J. Matunis, Catherine M. Guzzo and Young Ho Kim and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Biochemical and Biophysical Research Communications.

In The Last Decade

Ki Sa Sung

17 papers receiving 601 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Ki Sa Sung 533 192 120 77 76 18 606
Ok Sun Bang 474 0.9× 165 0.9× 91 0.8× 73 0.9× 59 0.8× 11 628
Karim Nacerddine 878 1.6× 265 1.4× 96 0.8× 56 0.7× 86 1.1× 10 941
Neri Minsky 827 1.6× 220 1.1× 101 0.8× 72 0.9× 75 1.0× 11 977
Sara Mari 547 1.0× 232 1.2× 89 0.7× 77 1.0× 108 1.4× 8 677
Harasim Thomas 755 1.4× 233 1.2× 46 0.4× 31 0.4× 84 1.1× 7 841
Thang Van Nguyen 477 0.9× 194 1.0× 46 0.4× 35 0.5× 78 1.0× 12 581
Claire Heride 541 1.0× 152 0.8× 81 0.7× 114 1.5× 63 0.8× 7 636
Aiqin Sun 364 0.7× 125 0.7× 88 0.7× 113 1.5× 67 0.9× 29 499
Dongxue Su 570 1.1× 216 1.1× 77 0.6× 61 0.8× 112 1.5× 12 691
Mark A. Villamil 627 1.2× 264 1.4× 92 0.8× 89 1.2× 87 1.1× 10 669

Countries citing papers authored by Ki Sa Sung

Since Specialization
Citations

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

Fields of papers citing papers by Ki Sa Sung

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ki Sa Sung. 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 Ki Sa Sung. The network helps show where Ki Sa Sung may publish in the future.

Co-authorship network of co-authors of Ki Sa Sung

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

All Works

18 of 18 papers shown
1.
Kim, Sung Tae, Ki Sa Sung, Dae-Ho Kim, et al.. (2024). The N-degron pathway mediates the autophagic degradation of cytosolic mitochondrial DNA during sterile innate immune responses. Cell Reports. 44(1). 115094–115094.
2.
Sung, Ki Sa, Sang Jun Han, Ji-Hye Lee, et al.. (2024). Identification of Plasma Protein Biomarkers for Predicting Lung Cancer. Anticancer Research. 44(11). 5147–5155. 2 indexed citations
3.
Sung, Ki Sa, et al.. (2019). Functional impairment of the HIPK2 small ubiquitin-like modifier (SUMO)-interacting motif in acute myeloid leukemia.. PubMed. 9(1). 94–107. 8 indexed citations
4.
Yoo, Young Dong, Dae‐Hee Lee, Hyunjoo Cha‐Molstad, et al.. (2016). Glioma‐derived cancer stem cells are hypersensitive to proteasomal inhibition. EMBO Reports. 18(1). 150–168. 31 indexed citations
5.
Cha‐Molstad, Hyunjoo, Ji Eun Yu, Su Hyun Lee, et al.. (2016). Modulation of SQSTM1/p62 activity by N-terminal arginylation of the endoplasmic reticulum chaperone HSPA5/GRP78/BiP. Autophagy. 12(2). 426–428. 27 indexed citations
6.
Lee, Dae‐Hee, Ki Sa Sung, Zong Sheng Guo, et al.. (2015). TRAIL‐Induced Caspase Activation Is a Prerequisite for Activation of the Endoplasmic Reticulum Stress‐Induced Signal Transduction Pathways. Journal of Cellular Biochemistry. 117(5). 1078–1091. 12 indexed citations
7.
Lee, Dae-Hee, Ki Sa Sung, David L. Bartlett, Yong Tae Kwon, & Yong J. Lee. (2014). HSP90 inhibitor NVP-AUY922 enhances TRAIL-induced apoptosis by suppressing the JAK2-STAT3-Mcl-1 signal transduction pathway in colorectal cancer cells. Cellular Signalling. 27(2). 293–305. 43 indexed citations
8.
Kim, Sung Tae, Takafumi Tasaki, Adriana Zakrzewska, et al.. (2013). The N-end rule proteolytic system in autophagy. Autophagy. 9(7). 1100–1103. 25 indexed citations
9.
Kim, Hana, et al.. (2013). Cell cycle-dependent SUMO-1 conjugation to nuclear mitotic apparatus protein (NuMA). Biochemical and Biophysical Research Communications. 443(1). 259–265. 9 indexed citations
10.
Tasaki, Takafumi, Sung Tae Kim, Adriana Zakrzewska, et al.. (2013). UBR box N-recognin-4 (UBR4), an N-recognin of the N-end rule pathway, and its role in yolk sac vascular development and autophagy. Proceedings of the National Academy of Sciences. 110(10). 3800–3805. 61 indexed citations
11.
Park, Sang‐Joon, Ki Sa Sung, Sean Bong Lee, et al.. (2011). Mdm2 associates with Ras effector NORE1 to induce the degradation of oncoprotein HIPK1. EMBO Reports. 13(2). 163–169. 24 indexed citations
12.
Sung, Ki Sa, et al.. (2010). Role of the SUMO-interacting motif in HIPK2 targeting to the PML nuclear bodies and regulation of p53. Experimental Cell Research. 317(7). 1060–1070. 42 indexed citations
13.
Kim, Jun Hwan, Ki Sa Sung, Su Myung Jung, et al.. (2010). Pellino-1, an Adaptor Protein of Interleukin-1 Receptor/Toll-like Receptor Signaling, Is Sumoylated by Ubc9. Molecules and Cells. 31(1). 85–90. 12 indexed citations
14.
Kim, Eun‐A, Ji Eon Kim, Ki Sa Sung, et al.. (2010). Homeodomain-interacting protein kinase 2 (HIPK2) targets β-catenin for phosphorylation and proteasomal degradation. Biochemical and Biophysical Research Communications. 394(4). 966–971. 35 indexed citations
15.
Zhu, Jianmei, Shanshan Zhu, Catherine M. Guzzo, et al.. (2008). Small Ubiquitin-related Modifier (SUMO) Binding Determines Substrate Recognition and Paralog-selective SUMO Modification. Journal of Biological Chemistry. 283(43). 29405–29415. 115 indexed citations
16.
Choi, Dong Wook, et al.. (2007). Ubiquitination and Degradation of Homeodomain-interacting Protein Kinase 2 by WD40 Repeat/SOCS Box Protein WSB-1. Journal of Biological Chemistry. 283(8). 4682–4689. 88 indexed citations
17.
Sung, Ki Sa, Yoon Young Go, Jin‐Hyun Ahn, et al.. (2005). Differential interactions of the homeodomain‐interacting protein kinase 2 (HIPK2) by phosphorylation‐dependent sumoylation. FEBS Letters. 579(14). 3001–3008. 32 indexed citations
18.
Kim, Young Ho, Young Ho Kim, Ki Sa Sung, et al.. (2005). Desumoylation of homeodomain‐interacting protein kinase 2 (HIPK2) through the cytoplasmic‐nuclear shuttling of the SUMO‐specific protease SENP1. FEBS Letters. 579(27). 6272–6278. 40 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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