Yayoi Kimura
Impact in
- Cell Biology top 2%
- Endoplasmic Reticulum Stress and Disease
- Cellular transport and secretion
- Physiology top 2%
- Calcium signaling and nucleotide metabolism
Papers in
- Cell Biology 15
- Muscle metabolism and nutrition 5
-
- Ubiquitin and proteasome pathways 9
- Glycosylation and Glycoproteins Research 9
- RNA and protein synthesis mechanisms 7
- Co-authors
- Hisashi HiranoYoshinori OhsumiYu OikawaHitoshi NakatogawaHiromi KirisakoKeisuke MochidaHayashi YamamotoS. Suzuki
- Journals
- Journal of Proteomics (11 papers)PROTEOMICS (8 papers)Anticancer Research (5 papers)Journal of Proteome Research (3 papers)The Journal of Cell Biology (3 papers)
- Partner nations
- JapanUnited StatesChina
In The Last Decade
Yayoi Kimura
86 papers receiving 2.4k citations
Hit Papers
Peers
Comparison fields: 5 of 107
- Cell Biology 738
- Physiology 136
- Epidemiology 982
- Molecular Biology 1.4k
- Aging 26
Countries citing papers authored by Yayoi Kimura
This map shows the geographic impact of Yayoi Kimura'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 Yayoi Kimura with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yayoi Kimura more than expected).
Fields of papers citing papers by Yayoi Kimura
This network shows the impact of papers produced by Yayoi Kimura. 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 Yayoi Kimura. The network helps show where Yayoi Kimura may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Yayoi Kimura, 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 | 1 | |
| 2 | 2024 | 1 | |
| 3 | 2024 | 1 | |
| 4 | 2024 | 1 | |
| 5 | 2024 | 1 | |
| 6 | 2024 | 1 | |
| 7 | 2023 | 1 | |
| 8 | 2023 | 4 | |
| 9 | 2023 | 3 | |
| 10 | 2021 | 2 | |
| 11 | 2019 | 18 | |
| 12 | 2019 | 9 | |
| 13 | 2019 | 15 | |
| 14 | 2018 | 12 | |
| 15 | 2017 | 49 | |
| 16 | 2016 | 48 | |
| 17 | 2014 | 18 | |
| 18 | 2012 | 1 | |
| 19 | 2010 | 29 | |
| 20 | 2000 | 95 |
About Yayoi Kimura
Yayoi Kimura is a scholar working on Cell Biology, Molecular Biology, Physiology, Oncology and Virology, having authored 88 papers that have together received 2.4k indexed citations. Recurring topics across this work include Peptidase Inhibition and Analysis (10 papers), Ubiquitin and proteasome pathways (9 papers), Glycosylation and Glycoproteins Research (9 papers), RNA and protein synthesis mechanisms (7 papers), Monoclonal and Polyclonal Antibodies Research (7 papers), Autophagy in Disease and Therapy (7 papers), Advanced Proteomics Techniques and Applications (6 papers) and Muscle metabolism and nutrition (5 papers). The work is most often cited by research in Cell Biology (738 citations), Physiology (136 citations), Epidemiology (982 citations), Molecular Biology (1.4k citations) and Aging (26 citations). Yayoi Kimura has collaborated with scholars based in Japan, United States and China. Frequent co-authors include Hisashi Hirano, Yoshinori Ohsumi, Yu Oikawa, Hitoshi Nakatogawa, Hiromi Kirisako, Keisuke Mochida, Hayashi Yamamoto, S. Suzuki, Chika Kondo‐Kakuta and Nobuo N. Noda. Their work appears in journals such as Journal of Proteomics, PROTEOMICS, Anticancer Research, Journal of Proteome Research and The Journal of Cell Biology.
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.