Kwang‐Su Park

3.2k citations
89 papers · 2.4k indexed · 1 hit paper · h-index 25
Topics
Protein Degradation and Inhibitors (16 papers)Ubiquitin and proteasome pathways (11 papers)Peptidase Inhibition and Analysis (7 papers)

In The Last Decade

Kwang‐Su Park

85 papers receiving 2.3k citations

Hit Papers

Advancing targeted protein degradation for cancer therapy20212026202220242021100200300400

Peers

Kwang‐Su Park
Comparison fields: 5 of 142
  • Molecular Biology 1.6k
  • Oncology 439
  • Organic Chemistry 202
  • Hematology 186
  • Pharmacology 118
Replace Madhumita Chatterjee with:
Madhumita Chatterjee India
Stefano Tiziani United States
Xiaodong Ma China
Dennis M. Miller United States
Yuqing Yang China
Yang Tang China
Shuxing Zhang United States
Jinghui Luo Switzerland
Xi Zhang China
Chenghong Zhang China
Kwang‐Su Park relative to Madhumita Chatterjee India Madhumita Chatterjee's profile →
Citations per field
00.5×2.8×
Madhumita Chatterjee · 1×
Citations per year

Countries citing papers authored by Kwang‐Su Park

Since Specialization
Citations

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

Fields of papers citing papers by Kwang‐Su Park

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kwang‐Su 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 Kwang‐Su Park. The network helps show where Kwang‐Su Park may publish in the future.

Co-authorship network of co-authors of Kwang‐Su Park

This figure shows the co-authorship network connecting the top 25 collaborators of Kwang‐Su Park. A scholar is included among the top collaborators of Kwang‐Su 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 Kwang‐Su Park. Kwang‐Su 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
#WorkIndexed citations
1 0
2 0
3 2
4 26
5 39
6 32
7 96
8 91
9
Advancing targeted protein degradation for cancer therapybreakdown →
425
10 3
11 2
12 46
13 1
14
Physicochemical characteristics and electric conductivity of various fruit wines.
12
15 8
16 6
17 12
18 14
19
S-adenosyl-L-methionine analogues to enhance the production of actinorhodin
2
20
The Comparison and Use of Yield Models in Semiconductor Manufacturing
1

About Kwang‐Su Park

Kwang‐Su Park is a scholar working on Biochemistry, Virology and Hepatology, having authored 89 papers that have together received 2.4k indexed citations. Recurring topics across this work include Protein Degradation and Inhibitors (16 papers), Ubiquitin and proteasome pathways (11 papers) and Peptidase Inhibition and Analysis (7 papers). The work is most often cited by research in Molecular Biology (1.6k citations), Hematology (186 citations) and Oncology (439 citations). Kwang‐Su Park has collaborated with scholars based in South Korea, United States and Japan. Frequent co-authors include Jian Jin, Youhoon Chong, H. Ümit Kanıskan, Brandon Dale, Yue Xiong, Meng Cheng, Hyunah Choo, Mi Kyoung Kim, Mi Kyoung Kim and Gang Greg Wang. Their work appears in journals such as Journal of the American Chemical Society, Nucleic Acids Research and Nature reviews. Cancer.

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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