Ken Nishimura
Impact in
- Molecular Biology top 5%
- Pluripotent Stem Cells Research
- CRISPR and Genetic Engineering
- Renal and related cancers
- Hematology top 5%
Papers in
-
- Pluripotent Stem Cells Research 31
- CRISPR and Genetic Engineering 24
- RNA Interference and Gene Delivery 6
- Genetics 12
- Animal Genetics and Reproduction 5
- Virus-based gene therapy research 4
- Co-authors
- Mahito Nakanishi (38 shared papers)Manami Ohtaka (30 shared papers)Koji Hisatake (19 shared papers)Aya Fukuda (17 shared papers)Hiromitsu Nakauchi (6 shared papers)Keiji Ueda (5 shared papers)Koichi Yamanishi (5 shared papers)Kazuei Igarashi (4 shared papers)
- Journals
- Stem Cell Reports (6 papers)Scientific Reports (5 papers)PLoS ONE (4 papers)In Vitro Cellular & Developmental Biology - Animal (3 papers)Journal of Biological Chemistry (3 papers)
- Partner nations
- JapanUnited StatesIndia
In The Last Decade
Ken Nishimura
65 papers receiving 2.3k citations
Peers
Comparison fields: 5 of 111
- Molecular Biology 1.6k
- Hematology 167
- Oncology 352
- Hepatology 99
- Genetics 126
Countries citing papers authored by Ken Nishimura
This map shows the geographic impact of Ken Nishimura'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 Ken Nishimura with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ken Nishimura more than expected).
Fields of papers citing papers by Ken Nishimura
This network shows the impact of papers produced by Ken Nishimura. 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 Ken Nishimura. The network helps show where Ken Nishimura may publish in the future.
Co-authors
The 25 scholars most cited alongside Ken Nishimura, 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 65 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2010 | 296 | |
| 2 | 2010 | 262 | |
| 3 | 2016 | 194 | |
| 4 | 2014 | 166 | |
| 5 | 2004 | 82 | |
| 6 | 2016 | 78 | |
| 7 | 2015 | 73 | |
| 8 | 2016 | 72 | |
| 9 | 2019 | 60 | |
| 10 | 2017 | 59 | |
| 11 | 2013 | 58 | |
| 12 | 2013 | 56 | |
| 13 | 2002 | 51 | |
| 14 | 1998 | 49 | |
| 15 | 2015 | 43 | |
| 16 | 1996 | 41 | |
| 17 | 2007 | 38 | |
| 18 | 2014 | 37 | |
| 19 | 2015 | 37 | |
| 20 | 2005 | 37 |
About Ken Nishimura
Ken Nishimura is a scholar working on Molecular Biology, Genetics, Oncology, Epidemiology and Genetics, having authored 65 papers that have together received 2.4k indexed citations. Recurring topics across this work include Pluripotent Stem Cells Research (31 papers), CRISPR and Genetic Engineering (24 papers), RNA Interference and Gene Delivery (6 papers), Viral-associated cancers and disorders (6 papers), Animal Genetics and Reproduction (5 papers), Cytomegalovirus and herpesvirus research (5 papers), 3D Printing in Biomedical Research (4 papers) and Virus-based gene therapy research (4 papers). The work is most often cited by research in Molecular Biology (1.6k citations), Hematology (167 citations), Oncology (352 citations), Hepatology (99 citations) and Genetics (126 citations). Ken Nishimura has collaborated with scholars based in Japan, United States and India. Frequent co-authors include Mahito Nakanishi, Manami Ohtaka, Koji Hisatake, Aya Fukuda, Hiromitsu Nakauchi, Keiji Ueda, Koichi Yamanishi, Kazuei Igarashi, Yoshimi Kakinuma and Shuhei Sakakibara. Their work appears in journals such as Stem Cell Reports, Scientific Reports, PLoS ONE, In Vitro Cellular & Developmental Biology - Animal and Journal of Biological Chemistry.
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.