Dae Kyong Kim

2.1k total citations
74 papers, 1.7k citations indexed

About

Dae Kyong Kim is a scholar working on Molecular Biology, Cell Biology and Pathology and Forensic Medicine. According to data from OpenAlex, Dae Kyong Kim has authored 74 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 49 papers in Molecular Biology, 14 papers in Cell Biology and 8 papers in Pathology and Forensic Medicine. Recurrent topics in Dae Kyong Kim's work include Sphingolipid Metabolism and Signaling (17 papers), Lipid Membrane Structure and Behavior (11 papers) and Protein Kinase Regulation and GTPase Signaling (9 papers). Dae Kyong Kim is often cited by papers focused on Sphingolipid Metabolism and Signaling (17 papers), Lipid Membrane Structure and Behavior (11 papers) and Protein Kinase Regulation and GTPase Signaling (9 papers). Dae Kyong Kim collaborates with scholars based in South Korea, United States and Japan. Dae Kyong Kim's co-authors include Keizo Inoue, Ichiro Kudo, Mi‐Ock Lee, Kwang‐Mook Jung, Hyunsung Park, Sung Yun Jung, Jong Hoon Won, Young‐Gun Yoo, Jong Min Choi and Joseph V. Bonventre and has published in prestigious journals such as Journal of Biological Chemistry, PLoS ONE and PLANT PHYSIOLOGY.

In The Last Decade

Dae Kyong Kim

73 papers receiving 1.7k citations

Peers

Dae Kyong Kim
Comparison fields: 5 of 118
  • Molecular Biology 961
  • Cell Biology 251
  • Physiology 229
  • Cancer Research 202
  • Epidemiology 194
Replace Yenshou Lin with:
Yenshou Lin Taiwan
Satoshi Akiba Japan
Yoon Sin Oh South Korea
Alan A. Sneddon United Kingdom
Kan Liao China
Yumei Wang China
Ok‐Sun Bang South Korea
Sujoy Bhattacharya United States
Toshihiko Aki Japan
Jae‐Won Soh South Korea
Yenshou Lin Taiwan View profile →
Citations per field, relative to Dae Kyong Kim
Dae Kyong Kim · 1×
Citations per year, relative to Dae Kyong Kim
Dae Kyong Kim · 1×

Countries citing papers authored by Dae Kyong Kim

Since Specialization
Citations

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

Fields of papers citing papers by Dae Kyong Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dae Kyong 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 Dae Kyong Kim. The network helps show where Dae Kyong Kim may publish in the future.

Co-authorship network of co-authors of Dae Kyong Kim

This figure shows the co-authorship network connecting the top 25 collaborators of Dae Kyong Kim. A scholar is included among the top collaborators of Dae Kyong 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 Dae Kyong Kim. Dae Kyong Kim 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
# Work Indexed citations
1 3
2 4
3 1
4 6
5 3
6 2
7 4
8 21
9 9
10 9
11 2
12 146
13 13
14 8
15 36
16 65
17 38
18
Inhibition of a Neutral Form of Sphingomyelinase by Alkylthioureido-1,3-propandiols, KY353X Series
1
19 98
20 29

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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