Emi Ito
Impact in
- Cell Biology top 2%
- Cellular transport and secretion
- Molecular Biology top 5%
- Plant Reproductive Biology
- DNA Repair Mechanisms
- Photosynthetic Processes and Mechanisms
Papers in
-
- Plant Reproductive Biology 8
- Receptor Mechanisms and Signaling 7
- Photosynthetic Processes and Mechanisms 5
- Oncology 16
- Co-authors
- Takashi Ueda (14 shared papers)Akihiko Nakano (12 shared papers)Yuka Yanagisawa (24 shared papers)Kazuo Ebine (9 shared papers)Tomohiro Uemura (8 shared papers)Shinya Watanabe (27 shared papers)Tatsuaki Goh (5 shared papers)Kazuo Maruyama (11 shared papers)
- Journals
- Biochemical and Biophysical Research Communications (6 papers)Journal of Biological Chemistry (4 papers)Gene (4 papers)Journal of Molecular Biology (3 papers)FEBS Letters (3 papers)
- Partner nations
- JapanUnited StatesUnited Kingdom
In The Last Decade
Emi Ito
113 papers receiving 3.8k citations
Peers
Comparison fields: 5 of 157
- Cell Biology 640
- Molecular Biology 2.1k
- Cancer Research 431
- Plant Science 985
- Oncology 563
Countries citing papers authored by Emi Ito
This map shows the geographic impact of Emi Ito'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 Emi Ito with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Emi Ito more than expected).
Fields of papers citing papers by Emi Ito
This network shows the impact of papers produced by Emi Ito. 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 Emi Ito. The network helps show where Emi Ito may publish in the future.
Co-authors
The 25 scholars most cited alongside Emi Ito, 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 119 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2013 | 278 | |
| 2 | 2002 | 235 | |
| 3 | 2011 | 222 | |
| 4 | 2008 | 150 | |
| 5 | 2006 | 133 | |
| 6 | 2001 | 132 | |
| 7 | 2014 | 115 | |
| 8 | 2018 | 114 | |
| 9 | 2007 | 114 | |
| 10 | 2009 | 112 | |
| 11 | 2018 | 107 | |
| 12 | 2011 | 101 | |
| 13 | 2012 | 87 | |
| 14 | 1999 | 82 | |
| 15 | 2005 | 72 | |
| 16 | 2021 | 71 | |
| 17 | 2014 | 65 | |
| 18 | 2020 | 59 | |
| 19 | 2006 | 57 | |
| 20 | 2011 | 55 |
About Emi Ito
Emi Ito is a scholar working on Molecular Biology, Oncology, Cell Biology, Epidemiology and Pathology and Forensic Medicine, having authored 119 papers that have together received 3.8k indexed citations. Recurring topics across this work include Cellular transport and secretion (11 papers), Plant Reproductive Biology (8 papers), Receptor Mechanisms and Signaling (7 papers), Cancer Genomics and Diagnostics (6 papers), Neuropeptides and Animal Physiology (5 papers), Photosynthetic Processes and Mechanisms (5 papers), Liver Disease Diagnosis and Treatment (5 papers) and Dementia and Cognitive Impairment Research (5 papers). The work is most often cited by research in Cell Biology (640 citations), Molecular Biology (2.1k citations), Cancer Research (431 citations), Plant Science (985 citations) and Oncology (563 citations). Emi Ito has collaborated with scholars based in Japan, United States and United Kingdom. Frequent co-authors include Takashi Ueda, Akihiko Nakano, Yuka Yanagisawa, Kazuo Ebine, Tomohiro Uemura, Shinya Watanabe, Tatsuaki Goh, Kazuo Maruyama, Reiko Honma and Masaru Fujimoto. Their work appears in journals such as Biochemical and Biophysical Research Communications, Journal of Biological Chemistry, Gene, Journal of Molecular Biology and FEBS Letters.
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.