Aika Nojima
Impact in
- Aging top 2%
- Genetics, Aging, and Longevity in Model Organisms
- Physiology top 5%
- Adipose Tissue and Metabolism
- Telomeres, Telomerase, and Senescence
Papers in
-
- Metabolism, Diabetes, and Cancer 3
- Peroxisome Proliferator-Activated Receptors 1
- Angiogenesis and VEGF in Cancer 1
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- Adipose Tissue and Metabolism 5
- Telomeres, Telomerase, and Senescence 2
- Co-authors
- Tohru Minamino (13 shared papers)Ippei Shimizu (11 shared papers)Masataka Yokoyama (10 shared papers)Issei Komuro (8 shared papers)Takashi Ito (4 shared papers)Junji Moriya (10 shared papers)Sho Okada (10 shared papers)Masayuki Orimo (2 shared papers)
- Journals
- Cell Metabolism (3 papers)PLoS ONE (3 papers)Circulation Research (2 papers)Nature Medicine (1 paper)Cell Reports (1 paper)
- Partner nations
- JapanUnited StatesAustria
In The Last Decade
Aika Nojima
13 papers receiving 1.7k citations
Aika Nojima's Hit Papers
Peers
Comparison fields: 5 of 90
- Aging 128
- Physiology 650
- Cardiology and Cardiovascular Medicine 289
- Cancer Research 187
- Geriatrics and Gerontology 34
Countries citing papers authored by Aika Nojima
This map shows the geographic impact of Aika Nojima'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 Aika Nojima with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Aika Nojima more than expected).
Fields of papers citing papers by Aika Nojima
This network shows the impact of papers produced by Aika Nojima. 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 Aika Nojima. The network helps show where Aika Nojima may publish in the future.
Co-authors
The 25 scholars most cited alongside Aika Nojima, 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 | A crucial role for adipose tissue p53 in the regulation of insulin resistance Hit paper breakdown → | 2009 | 684 |
| 2 | 2010 | 177 | |
| 3 | 2012 | 150 | |
| 4 | 2009 | 130 | |
| 5 | 2012 | 116 | |
| 6 | 2013 | 107 | |
| 7 | 2014 | 95 | |
| 8 | 2009 | 60 | |
| 9 | 2013 | 59 | |
| 10 | 2008 | 48 | |
| 11 | 2014 | 48 | |
| 12 | 2014 | 29 | |
| 13 | 2012 | 5 |
About Aika Nojima
Aika Nojima is a scholar working on Molecular Biology, Physiology, Epidemiology, Cardiology and Cardiovascular Medicine and Cancer Research, having authored 13 papers that have together received 1.7k indexed citations. Recurring topics across this work include Adipose Tissue and Metabolism (5 papers), Adipokines, Inflammation, and Metabolic Diseases (4 papers), Metabolism, Diabetes, and Cancer (3 papers), Telomeres, Telomerase, and Senescence (2 papers), Axon Guidance and Neuronal Signaling (2 papers), Cancer, Hypoxia, and Metabolism (2 papers), Peroxisome Proliferator-Activated Receptors (1 paper) and Angiogenesis and VEGF in Cancer (1 paper). The work is most often cited by research in Aging (128 citations), Physiology (650 citations), Cardiology and Cardiovascular Medicine (289 citations), Cancer Research (187 citations) and Geriatrics and Gerontology (34 citations). Aika Nojima has collaborated with scholars based in Japan, United States and Austria. Frequent co-authors include Tohru Minamino, Ippei Shimizu, Masataka Yokoyama, Issei Komuro, Takashi Ito, Junji Moriya, Sho Okada, Masayuki Orimo, Yuichi Oike and Takeshige Kunieda. Their work appears in journals such as Cell Metabolism, PLoS ONE, Circulation Research, Nature Medicine and Cell Reports.
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.