A. Naka
Impact in
-
- Adipose Tissue and Metabolism
-
- Phytoestrogen effects and research
Papers in
-
- Metabolism, Diabetes, and Cancer 2
- Ubiquitin and proteasome pathways 2
- Oncology 6
- Drug Transport and Resistance Mechanisms 4
- Co-authors
- Kaoruko Iida (7 shared papers)Yuri Sakamoto (4 shared papers)Kazuo Kondo (4 shared papers)Masaki Horie (3 shared papers)Shingo Kamoshida (5 shared papers)Naoshi Obara (1 shared paper)Ken Matsumoto (1 shared paper)Masatsugu Ema (1 shared paper)
In The Last Decade
A. Naka
16 papers receiving 481 citations
Peers
Comparison fields: 5 of 79
- Physiology 125
- Pathology and Forensic Medicine 80
- Cell Biology 70
- Geriatrics and Gerontology 16
- Cancer Research 57
Countries citing papers authored by A. Naka
This map shows the geographic impact of A. Naka'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 A. Naka with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites A. Naka more than expected).
Fields of papers citing papers by A. Naka
This network shows the impact of papers produced by A. Naka. 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 A. Naka. The network helps show where A. Naka may publish in the future.
Co-authors
The 25 scholars most cited alongside A. Naka, 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 | 2016 | 74 | |
| 2 | 2013 | 60 | |
| 3 | 2018 | 51 | |
| 4 | 2015 | 45 | |
| 5 | 2009 | 42 | |
| 6 | 2015 | 37 | |
| 7 | 2009 | 35 | |
| 8 | 2012 | 29 | |
| 9 | 2013 | 29 | |
| 10 | High expression of organic anion transporter 2 and organic cation transporter 2 is an independent predictor of good outcomes in patients with metastatic colorectal cancer treated with FOLFOX-based chemotherapy. | 2014 | 23 |
| 11 | 2014 | 21 | |
| 12 | 2016 | 13 | |
| 13 | 2012 | 12 | |
| 14 | Organic cation transporter 2 for predicting cisplatin-based neoadjuvant chemotherapy response in gastric cancer. | 2015 | 12 |
| 15 | 2015 | 5 | |
| 16 | 2011 | 1 |
About A. Naka
A. Naka is a scholar working on Molecular Biology, Oncology, Physiology, Cancer Research and Epidemiology, having authored 16 papers that have together received 489 indexed citations. Recurring topics across this work include Adipose Tissue and Metabolism (4 papers), Drug Transport and Resistance Mechanisms (4 papers), Adipokines, Inflammation, and Metabolic Diseases (3 papers), Metabolism, Diabetes, and Cancer (2 papers), Cholangiocarcinoma and Gallbladder Cancer Studies (2 papers), Cancer, Hypoxia, and Metabolism (2 papers), Muscle metabolism and nutrition (2 papers) and Ubiquitin and proteasome pathways (2 papers). The work is most often cited by research in Physiology (125 citations), Pathology and Forensic Medicine (80 citations), Cell Biology (70 citations), Geriatrics and Gerontology (16 citations) and Cancer Research (57 citations). A. Naka has collaborated with scholars based in Japan and Australia. Frequent co-authors include Kaoruko Iida, Yuri Sakamoto, Kazuo Kondo, Masaki Horie, Shingo Kamoshida, Naoshi Obara, Ken Matsumoto, Masatsugu Ema, Satoru Takahashi and Shigehiko Imagawa. Their work appears in journals such as Molecular Nutrition & Food Research, International Journal of Sports Medicine, American Journal of Physiology-Endocrinology and Metabolism, Endocrinology and Histopathology.
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.