Joungmok Kim
- Molecular Biology top 0.5%
- Epidemiology top 0.1%
- Cell Biology top 0.1%
- Physiology top 1%
- Cancer Research top 1%
- Co-authors
- Kun‐Liang GuanBenoı̂t ViolletMondira KunduJoohun HaBin ZhaoKen InokiJindan YuArul M. Chinnaiyan
- Topics
- Autophagy in Disease and Therapy (17 papers)Metabolism, Diabetes, and Cancer (14 papers)Bacillus and Francisella bacterial research (10 papers)
- Cited by
- Cell BiologyPhysiologyEpidemiology
- Partner nations
- South KoreaUnited StatesFrance
In The Last Decade
Joungmok Kim
50 papers receiving 15.1k citations
Hit Papers
Peers
Comparison fields: 5 of 132
- Molecular Biology 8.7k
- Epidemiology 6.7k
- Cell Biology 4.2k
- Physiology 1.6k
- Cancer Research 1.5k
Countries citing papers authored by Joungmok Kim
This map shows the geographic impact of Joungmok 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 Joungmok Kim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Joungmok Kim more than expected).
Fields of papers citing papers by Joungmok Kim
This network shows the impact of papers produced by Joungmok 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 Joungmok Kim. The network helps show where Joungmok Kim may publish in the future.
Co-authorship network of co-authors of Joungmok Kim
This figure shows the co-authorship network connecting the top 25 collaborators of Joungmok Kim. A scholar is included among the top collaborators of Joungmok 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 Joungmok Kim. Joungmok Kim is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | mTOR as a central hub of nutrient signalling and cell growthbreakdown → | 757 |
| 3 | 126 | |
| 4 | AMPK activators: mechanisms of action and physiological activitiesbreakdown → | 599 |
| 5 | 3 | |
| 6 | 29 | |
| 7 | 11 | |
| 8 | Differential Regulation of Distinct Vps34 Complexes by AMPK in Nutrient Stress and Autophagybreakdown → | 642 |
| 9 | 8 | |
| 10 | 4 | |
| 11 | 21 | |
| 12 | The autophagy initiating kinase ULK1 is regulated via opposing phosphorylation by AMPK and mTORbreakdown → | 493 |
| 13 | 33 | |
| 14 | The role of YAP transcription coactivator in regulating stem cell self-renewal and differentiationbreakdown → | 605 |
| 15 | 2 | |
| 16 | 7 | |
| 17 | Screening of Peptides Bound to Anthrax Protective Antigen by Phage Display | 14 |
| 18 | 9 | |
| 19 | 8 | |
| 20 | 74 |
About Joungmok Kim
Joungmok Kim is a scholar working on Physiology, Geriatrics and Gerontology and Molecular Biology, having authored 50 papers that have together received 15.2k indexed citations. Recurring topics across this work include Autophagy in Disease and Therapy (17 papers), Metabolism, Diabetes, and Cancer (14 papers) and Bacillus and Francisella bacterial research (10 papers). The work is most often cited by research in Cell Biology (4.2k citations), Physiology (1.1k citations) and Epidemiology (6.7k citations). Joungmok Kim has collaborated with scholars based in South Korea, United States and France. Frequent co-authors include Kun‐Liang Guan, Benoı̂t Viollet, Mondira Kundu, Joohun Ha, Bin Zhao, Ken Inoki, Jindan Yu, Arul M. Chinnaiyan, Ryan C. Russell and Zhi-Chun Lai. Their work appears in journals such as Cell, Advanced Materials and Journal of Biological Chemistry.
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.