Daiji Okamura

2.4k total citations
25 papers, 1.3k citations indexed

About

Daiji Okamura is a scholar working on Molecular Biology, Genetics and Surgery. According to data from OpenAlex, Daiji Okamura has authored 25 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Molecular Biology, 4 papers in Genetics and 3 papers in Surgery. Recurrent topics in Daiji Okamura's work include Pluripotent Stem Cells Research (20 papers), CRISPR and Genetic Engineering (14 papers) and Renal and related cancers (5 papers). Daiji Okamura is often cited by papers focused on Pluripotent Stem Cells Research (20 papers), CRISPR and Genetic Engineering (14 papers) and Renal and related cancers (5 papers). Daiji Okamura collaborates with scholars based in Japan, United States and Spain. Daiji Okamura's co-authors include Yasuhisa Matsui, Juan Carlos Izpisúa Belmonte, Keiichiro Suzuki, Jun Wu, Pablo J. Ross, Masahiro Sakurai, Y. S. Bogliotti, Marcela Vilariño, Min-Zu Wu and Núria Montserrat and has published in prestigious journals such as Nature, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Daiji Okamura

23 papers receiving 1.3k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Daiji Okamura Japan 16 1.1k 303 205 171 117 25 1.3k
Norah M. E. Fogarty United Kingdom 10 1.3k 1.2× 246 0.8× 337 1.6× 104 0.6× 125 1.1× 14 1.7k
Sanae Hamanaka Japan 13 965 0.9× 238 0.8× 101 0.5× 318 1.9× 91 0.8× 21 1.5k
Anna Piliszek Poland 15 1.5k 1.3× 239 0.8× 416 2.0× 158 0.9× 125 1.1× 26 1.6k
Kadue Takahashi Japan 8 1.5k 1.3× 241 0.8× 237 1.2× 104 0.6× 146 1.2× 10 1.7k
Misuzu Yamashita Japan 21 616 0.5× 254 0.8× 412 2.0× 97 0.6× 66 0.6× 26 1.2k
Steffen Biechele Canada 13 1.3k 1.1× 311 1.0× 145 0.7× 125 0.7× 77 0.7× 18 1.7k
Yair S. Manor Israel 5 800 0.7× 280 0.9× 167 0.8× 77 0.5× 43 0.4× 6 1.0k
Michiko Hirose Japan 23 1.2k 1.1× 461 1.5× 435 2.1× 134 0.8× 80 0.7× 55 1.6k
Shannon Eaker United States 13 479 0.4× 150 0.5× 159 0.8× 112 0.7× 114 1.0× 22 807
Zhongxia Qi United States 14 1.3k 1.2× 209 0.7× 72 0.4× 136 0.8× 125 1.1× 36 1.6k

Countries citing papers authored by Daiji Okamura

Since Specialization
Citations

This map shows the geographic impact of Daiji Okamura'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 Daiji Okamura with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daiji Okamura more than expected).

Fields of papers citing papers by Daiji Okamura

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daiji Okamura. 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 Daiji Okamura. The network helps show where Daiji Okamura may publish in the future.

Co-authorship network of co-authors of Daiji Okamura

This figure shows the co-authorship network connecting the top 25 collaborators of Daiji Okamura. A scholar is included among the top collaborators of Daiji Okamura based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Daiji Okamura. Daiji Okamura is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Schmitz, Daniel A., Seiya Oura, Yi Ding, et al.. (2025). Unraveling mitochondrial influence on mammalian pluripotency via enforced mitophagy. Cell. 188(17). 4773–4789.e22.
2.
Yamaguchi, Shinpei, et al.. (2024). Development of a chemically disclosed serum-free medium for mouse pluripotent stem cells. Frontiers in Bioengineering and Biotechnology. 12. 1390386–1390386. 2 indexed citations
3.
Okamura, Daiji, et al.. (2023). The ensured proliferative capacity of myoblast in serum-reduced conditions with Methyl-β-cyclodextrin. Frontiers in Cell and Developmental Biology. 11. 1193634–1193634. 4 indexed citations
4.
Wu, Jun, et al.. (2022). The amount of membrane cholesterol required for robust cell adhesion and proliferation in serum-free condition. PLoS ONE. 17(7). e0259482–e0259482. 9 indexed citations
5.
Okamura, Daiji, et al.. (2021). Stepwise conversion methods between ground states pluripotency from naïve to primed. Biochemical and Biophysical Research Communications. 574. 70–77. 3 indexed citations
6.
Angeles, Alejandro De Los, Daiji Okamura, & Jun Wu. (2019). Highly Efficient Derivation of Pluripotent Stem Cells from Mouse Preimplantation and Postimplantation Embryos in Serum-Free Conditions. Methods in molecular biology. 2005. 29–36. 4 indexed citations
7.
Bogliotti, Y. S., Jun Wu, Marcela Vilariño, et al.. (2018). Efficient derivation of stable primed pluripotent embryonic stem cells from bovine blastocysts. Proceedings of the National Academy of Sciences. 115(9). 2090–2095. 195 indexed citations
8.
Tando, Yukiko, et al.. (2018). Derivation of pluripotent stem cells from nascent undifferentiated teratoma. Developmental Biology. 446(1). 43–55. 5 indexed citations
9.
Wu, Jun, Marcela Vilariño, Keiichiro Suzuki, et al.. (2017). CRISPR-Cas9 mediated one-step disabling of pancreatogenesis in pigs. Scientific Reports. 7(1). 10487–10487. 39 indexed citations
10.
Hirasaki, Masataka, Tomoaki Hishida, Jun Wu, et al.. (2016). Loss of MAX results in meiotic entry in mouse embryonic and germline stem cells. Nature Communications. 7(1). 11056–11056. 59 indexed citations
11.
Xia, Yun, Emmanuel Nivet, Ignacio Sancho-Martinez, et al.. (2013). Directed differentiation of human pluripotent cells to ureteric bud kidney progenitor-like cells. Nature Cell Biology. 15(12). 1507–1515. 245 indexed citations
12.
Okamura, Daiji, Makiko Ikeda, Hiroko Kawaguchi, et al.. (2013). Max is a repressor of germ cell-related gene expression in mouse embryonic stem cells. Nature Communications. 4(1). 1754–1754. 61 indexed citations
13.
Leitch, Harry G., Daiji Okamura, Gabriela Durcova‐Hills, et al.. (2013). On the fate of primordial germ cells injected into early mouse embryos. Developmental Biology. 385(2). 155–159. 20 indexed citations
14.
Okamura, Daiji, Kentaro Mochizuki, Makiko Ikeda, et al.. (2012). REST and its downstream molecule Mek5 regulate survival of primordial germ cells. Developmental Biology. 372(2). 190–202. 13 indexed citations
15.
Okamura, Daiji, Makiko Ikeda, Keiko Ozato, et al.. (2012). Cell cycle gene-specific control of transcription has a critical role in proliferation of primordial germ cells. Genes & Development. 26(22). 2477–2482. 27 indexed citations
16.
Okamura, Daiji, et al.. (2008). Requirement of Oct3/4 function for germ cell specification. Developmental Biology. 317(2). 576–584. 48 indexed citations
17.
Matsui, Yasuhisa & Daiji Okamura. (2005). Mechanisms of germ-cell specification in mouse embryos. BioEssays. 27(2). 136–143. 35 indexed citations
18.
Kimura-Yoshida, Chiharu, Hiroshi Nakano, Daiji Okamura, et al.. (2005). Canonical Wnt Signaling and Its Antagonist Regulate Anterior-Posterior Axis Polarization by Guiding Cell Migration in Mouse Visceral Endoderm. Developmental Cell. 9(5). 639–650. 154 indexed citations
19.
Okamura, Daiji, Katsuhiko Hayashi, & Yasuhisa Matsui. (2004). Mouse epiblasts change responsiveness to BMP4 signal required for PGC formation through functions of extraembryonic ectoderm. Molecular Reproduction and Development. 70(1). 20–29. 37 indexed citations
20.
Huang, Ruo‐Pan, Tristan Darland, Daiji Okamura, Dan Mercola, & Eileen D. Adamson. (1994). Suppression of v-sis-dependent transformation by the transcription factor, Egr-1.. PubMed. 9(5). 1367–77. 70 indexed citations

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.

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