Ken Inoki
- Aging top 0.5%
- Molecular Biology top 0.2%
- PI3K/AKT/mTOR signaling in cancer 53
- Polyamine Metabolism and Applications 20
- Metabolism, Diabetes, and Cancer 12
- Physiology top 0.2%
- Tuberous Sclerosis Complex Research 15
- Cell Biology top 0.2%
- Cellular transport and secretion 12
- Geriatrics and Gerontology top 0.5%
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- Autophagy in Disease and Therapy 13
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- Mast cells and histamine 10
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- Pancreatic function and diabetes 8
- Co-authors
- Kun‐Liang GuanTianqing ZhuYong LiJun WuTianquan ZhuMichael N. CorradettiTian XuTsuneo Ikenoue
- Cited by
- AgingMolecular BiologyPhysiology
- Journals
- Journal of Biological Chemistry (9 papers)Proceedings of the National Academy of Sciences (5 papers)Journal of the American Society of Nephrology (4 papers)
- Partner nations
- United StatesJapanFrance
In The Last Decade
Ken Inoki
91 papers receiving 17.7k citations
Hit Papers
Peers
Comparison fields: 5 of 140
- Aging 460
- Molecular Biology 12.9k
- Physiology 701
- Cell Biology 2.4k
- Geriatrics and Gerontology 488
Countries citing papers authored by Ken Inoki
This map shows the geographic impact of Ken Inoki'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 Ken Inoki with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ken Inoki more than expected).
Fields of papers citing papers by Ken Inoki
This network shows the impact of papers produced by Ken Inoki. 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 Ken Inoki. The network helps show where Ken Inoki may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Ken Inoki, 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 | 2025 | 2 | |
| 2 | 2024 | 4 | |
| 3 | 2024 | 8 | |
| 4 | 2023 | 4 | |
| 5 | 2023 | 8 | |
| 6 | 2022 | 69 | |
| 7 | 2020 | 47 | |
| 8 | 2019 | 175 | |
| 9 | 2018 | 6 | |
| 10 | 2017 | 55 | |
| 11 | 2017 | 149 | |
| 12 | 2016 | 5 | |
| 13 | 2012 | 88 | |
| 14 | 2012 | 47 | |
| 15 | Spatial Coupling of mTOR and Autophagy Augments Secretory Phenotypesbreakdown → | 2011 | 459 |
| 16 | ATM signals to TSC2 in the cytoplasm to regulate mTORC1 in response to ROSbreakdown → | 2010 | 576 |
| 17 | 2007 | 130 | |
| 18 | 2006 | 16 | |
| 19 | 2004 | 198 | |
| 20 | 2003 | 139 |
About Ken Inoki
Ken Inoki is a scholar working on Nephrology, Cell Biology and Molecular Biology, having authored 92 papers that have together received 17.9k indexed citations. Recurring topics across this work include PI3K/AKT/mTOR signaling in cancer (53 papers), Polyamine Metabolism and Applications (20 papers), Tuberous Sclerosis Complex Research (15 papers), Autophagy in Disease and Therapy (13 papers), Metabolism, Diabetes, and Cancer (12 papers), Cellular transport and secretion (12 papers), Mast cells and histamine (10 papers) and Pancreatic function and diabetes (8 papers). The work is most often cited by research in Aging (460 citations), Molecular Biology (12.9k citations) and Physiology (701 citations). Ken Inoki has collaborated with scholars based in United States, Japan and France. Frequent co-authors include Kun‐Liang Guan, Tianqing Zhu, Yong Li, Jun Wu, Tianquan Zhu, Michael N. Corradetti, Tian Xu, Tsuneo Ikenoue, Qian Yang and Joungmok Kim. Their work appears in journals such as Journal of Biological Chemistry, Proceedings of the National Academy of Sciences, Journal of the American Society of Nephrology, Genes & Development and The EMBO Journal.
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.