Takehiro Noda
Impact in
- Hepatology top 1%
- Hepatocellular Carcinoma Treatment and Prognosis
- Cancer Research top 1%
- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
- Cancer, Hypoxia, and Metabolism
Papers in
- Co-authors
- Yuichiro� Doki (155 shared papers)Hidetoshi Eguchi (151 shared papers)Masaki Mori (65 shared papers)Daisaku Yamada (119 shared papers)Hiroshi Wada (65 shared papers)Kunihito Gotoh (90 shared papers)Shogo Kobayashi (130 shared papers)Yutaka Takeda (53 shared papers)
- Journals
- Annals of Surgical Oncology (21 papers)Annals of Gastroenterological Surgery (10 papers)Cancer Science (9 papers)Surgery Today (9 papers)Journal of Hepato-Biliary-Pancreatic Sciences (6 papers)
- Partner nations
- JapanUnited StatesThailand
In The Last Decade
Takehiro Noda
184 papers receiving 3.4k citations
Peers
Comparison fields: 5 of 109
- Hepatology 642
- Cancer Research 956
- Oncology 777
- Molecular Biology 1.3k
- Surgery 518
Countries citing papers authored by Takehiro Noda
This map shows the geographic impact of Takehiro Noda'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 Takehiro Noda with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Takehiro Noda more than expected).
Fields of papers citing papers by Takehiro Noda
This network shows the impact of papers produced by Takehiro Noda. 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 Takehiro Noda. The network helps show where Takehiro Noda may publish in the future.
Co-authors
The 25 scholars most cited alongside Takehiro Noda, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 210 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2010 | 290 | |
| 2 | 2017 | 222 | |
| 3 | 2007 | 180 | |
| 4 | 2018 | 111 | |
| 5 | 2009 | 100 | |
| 6 | 2021 | 93 | |
| 7 | 2011 | 78 | |
| 8 | 2017 | 69 | |
| 9 | 2011 | 69 | |
| 10 | 2018 | 62 | |
| 11 | 2016 | 60 | |
| 12 | 2016 | 58 | |
| 13 | 2006 | 57 | |
| 14 | 2009 | 53 | |
| 15 | 2016 | 52 | |
| 16 | 2017 | 51 | |
| 17 | 2018 | 51 | |
| 18 | 2016 | 49 | |
| 19 | 2019 | 49 | |
| 20 | 2019 | 48 |
About Takehiro Noda
Takehiro Noda is a scholar working on Oncology, Surgery, Hepatology, Molecular Biology and Epidemiology, having authored 210 papers that have together received 3.4k indexed citations. Recurring topics across this work include Pancreatic and Hepatic Oncology Research (43 papers), Hepatocellular Carcinoma Treatment and Prognosis (32 papers), Cholangiocarcinoma and Gallbladder Cancer Studies (21 papers), Cancer, Hypoxia, and Metabolism (9 papers), Organ Transplantation Techniques and Outcomes (7 papers), Gallbladder and Bile Duct Disorders (6 papers), Neuroendocrine Tumor Research Advances (6 papers) and Nutrition and Health in Aging (5 papers). The work is most often cited by research in Hepatology (642 citations), Cancer Research (956 citations), Oncology (777 citations), Molecular Biology (1.3k citations) and Surgery (518 citations). Takehiro Noda has collaborated with scholars based in Japan, United States and Thailand. Frequent co-authors include Yuichiro� Doki, Hidetoshi Eguchi, Masaki Mori, Daisaku Yamada, Hiroshi Wada, Kunihito Gotoh, Shogo Kobayashi, Yutaka Takeda, Tadafumi Asaoka and Hiroaki Nagano. Their work appears in journals such as Annals of Surgical Oncology, Annals of Gastroenterological Surgery, Cancer Science, Surgery Today and Journal of Hepato-Biliary-Pancreatic Sciences.
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.