Junko Masuda
Impact in
- Oncology top 10%
- Cancer Cells and Metastasis
- Cell Biology top 10%
- Cellular transport and secretion
- Hippo pathway signaling and YAP/TAZ
Papers in
-
- RNA Interference and Gene Delivery 4
- Oncology 9
- Cancer Cells and Metastasis 5
- Co-authors
- Masaharu Seno (14 shared papers)Tomonari Kasai (11 shared papers)Yoshiro Maru (3 shared papers)Ayano Satoh (12 shared papers)Akimasa Seno (9 shared papers)Arun Vaidyanath (8 shared papers)Neha Nair (4 shared papers)Akifumi Mizutani (10 shared papers)
- Journals
- Clinical & Experimental Immunology (4 papers)International Journal of Molecular Sciences (3 papers)Journal of Nuclear Materials (2 papers)Neuroscience (2 papers)Thrombosis Research (2 papers)
- Partner nations
- JapanUnited StatesEgypt
In The Last Decade
Junko Masuda
45 papers receiving 903 citations
Peers
Comparison fields: 5 of 108
- Oncology 250
- Cell Biology 126
- Cancer Research 104
- Molecular Biology 475
- Cellular and Molecular Neuroscience 118
Countries citing papers authored by Junko Masuda
This map shows the geographic impact of Junko Masuda'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 Junko Masuda with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Junko Masuda more than expected).
Fields of papers citing papers by Junko Masuda
This network shows the impact of papers produced by Junko Masuda. 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 Junko Masuda. The network helps show where Junko Masuda may publish in the future.
Co-authors
The 25 scholars most cited alongside Junko Masuda, 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 45 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 140 | |
| 2 | 2008 | 86 | |
| 3 | 2013 | 62 | |
| 4 | 2013 | 58 | |
| 5 | 2014 | 46 | |
| 6 | iPSC-derived cancer stem cells provide a model of tumor vasculature. | 2016 | 38 |
| 7 | 2004 | 31 | |
| 8 | 2010 | 31 | |
| 9 | 2005 | 28 | |
| 10 | 2018 | 28 | |
| 11 | 2005 | 27 | |
| 12 | 2005 | 24 | |
| 13 | 2016 | 23 | |
| 14 | 2018 | 21 | |
| 15 | 2005 | 21 | |
| 16 | 2004 | 20 | |
| 17 | 2018 | 19 | |
| 18 | 2016 | 18 | |
| 19 | 2008 | 17 | |
| 20 | 2019 | 17 |
About Junko Masuda
Junko Masuda is a scholar working on Molecular Biology, Oncology, Immunology, Hematology and Cell Biology, having authored 45 papers that have together received 920 indexed citations. Recurring topics across this work include Cancer Cells and Metastasis (5 papers), RNA Interference and Gene Delivery (4 papers), Blood Coagulation and Thrombosis Mechanisms (4 papers), Hippo pathway signaling and YAP/TAZ (4 papers), Nanoparticle-Based Drug Delivery (3 papers), Immune Response and Inflammation (3 papers), NF-κB Signaling Pathways (3 papers) and Immune cells in cancer (3 papers). The work is most often cited by research in Oncology (250 citations), Cell Biology (126 citations), Cancer Research (104 citations), Molecular Biology (475 citations) and Cellular and Molecular Neuroscience (118 citations). Junko Masuda has collaborated with scholars based in Japan, United States and Egypt. Frequent co-authors include Masaharu Seno, Tomonari Kasai, Yoshiro Maru, Ayano Satoh, Akimasa Seno, Arun Vaidyanath, Neha Nair, Akifumi Mizutani, Anna Sanchez Calle and Hiroshi Murakami. Their work appears in journals such as Clinical & Experimental Immunology, International Journal of Molecular Sciences, Journal of Nuclear Materials, Neuroscience and Thrombosis Research.
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.