Dae Kyong Kim
- Cell Biology top 5%
- Cellular transport and secretion 7
- Molecular Biology top 10%
- Sphingolipid Metabolism and Signaling 17
- Lipid Membrane Structure and Behavior 11
- Protein Kinase Regulation and GTPase Signaling 9
- Viral Infectious Diseases and Gene Expression in Insects 4
- Heme Oxygenase-1 and Carbon Monoxide 4
- Cancer Research top 10%
- Biochemistry top 5%
- Physiology top 10%
- Erythrocyte Function and Pathophysiology 3
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- Biomedical Research and Pathophysiology 5
- Co-authors
- Keizo InoueIchiro KudoMi‐Ock LeeKwang‐Mook JungHyunsung ParkSung Yun JungJong Hoon WonYoung‐Gun Yoo
- Partner nations
- South KoreaUnited StatesJapan
In The Last Decade
Dae Kyong Kim
73 papers receiving 1.7k citations
Peers
Comparison fields: 5 of 118
- Cell Biology 251
- Molecular Biology 961
- Cancer Research 202
- Biochemistry 93
- Physiology 229
Countries citing papers authored by Dae Kyong Kim
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
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
The 25 scholars most cited alongside Dae Kyong Kim, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 3 | |
| 2 | 2023 | 4 | |
| 3 | 2023 | 1 | |
| 4 | 2023 | 6 | |
| 5 | 2023 | 3 | |
| 6 | 2020 | 2 | |
| 7 | 2018 | 4 | |
| 8 | 2017 | 21 | |
| 9 | 2014 | 9 | |
| 10 | 2014 | 9 | |
| 11 | 2011 | 2 | |
| 12 | 2010 | 146 | |
| 13 | 2009 | 13 | |
| 14 | 2009 | 8 | |
| 15 | 2009 | 36 | |
| 16 | 2007 | 65 | |
| 17 | 2005 | 38 | |
| 18 | Inhibition of a Neutral Form of Sphingomyelinase by Alkylthioureido-1,3-propandiols, KY353X Series | 2003 | 1 |
| 19 | 2002 | 98 | |
| 20 | 1990 | 29 |
About Dae Kyong Kim
Dae Kyong Kim is a scholar working on Cell Biology, Molecular Biology and Physiology, having authored 74 papers that have together received 1.7k indexed citations. Recurring topics across this work include Sphingolipid Metabolism and Signaling (17 papers), Lipid Membrane Structure and Behavior (11 papers), Protein Kinase Regulation and GTPase Signaling (9 papers), Cellular transport and secretion (7 papers), Biomedical Research and Pathophysiology (5 papers), Viral Infectious Diseases and Gene Expression in Insects (4 papers), Heme Oxygenase-1 and Carbon Monoxide (4 papers) and Erythrocyte Function and Pathophysiology (3 papers). The work is most often cited by research in Cell Biology (251 citations), Molecular Biology (961 citations) and Cancer Research (202 citations). Dae Kyong Kim has collaborated with scholars based in South Korea, United States and Japan. Frequent 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. Their work appears in journals such as Journal of Biological Chemistry, PLoS ONE and PLANT PHYSIOLOGY.
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.