Youichi Naoe

744 total citations · 1 hit paper
9 papers, 573 citations indexed

About

Youichi Naoe is a scholar working on Molecular Biology, Oncology and Cell Biology. According to data from OpenAlex, Youichi Naoe has authored 9 papers receiving a total of 573 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 2 papers in Oncology and 2 papers in Cell Biology. Recurrent topics in Youichi Naoe's work include Signaling Pathways in Disease (2 papers), CRISPR and Genetic Engineering (2 papers) and Plant Molecular Biology Research (2 papers). Youichi Naoe is often cited by papers focused on Signaling Pathways in Disease (2 papers), CRISPR and Genetic Engineering (2 papers) and Plant Molecular Biology Research (2 papers). Youichi Naoe collaborates with scholars based in Japan. Youichi Naoe's co-authors include Hiroaki Kato, Makoto Matsuoka, Miyako Ueguchi‐Tanaka, Asako Shimada, Hiroko Ohmiya, Toru Nakatsu, Masatoshi Nakajima, Akitsu Hotta, Yukimasa Makita and Satoru Matsumoto and has published in prestigious journals such as Nature, Journal of Biological Chemistry and Nature Communications.

In The Last Decade

Youichi Naoe

9 papers receiving 565 citations

Hit Papers

Low immunogenicity of LNP allows repeated administrations... 2021 2026 2022 2024 2021 50 100 150 200

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Youichi Naoe Japan 7 415 267 73 39 34 9 573
Tomáš Mašek Czechia 14 510 1.2× 112 0.4× 54 0.7× 20 0.5× 18 0.5× 30 702
Jeffrey T. Irelan United States 10 456 1.1× 292 1.1× 43 0.6× 16 0.4× 44 1.3× 11 623
Weihua Pan China 13 594 1.4× 191 0.7× 91 1.2× 57 1.5× 12 0.4× 47 750
Changyou Li China 12 404 1.0× 191 0.7× 43 0.6× 22 0.6× 11 0.3× 51 591
Silke Busch Germany 15 634 1.5× 160 0.6× 86 1.2× 18 0.5× 67 2.0× 17 766
Amber Sorenson United States 3 252 0.6× 162 0.6× 100 1.4× 13 0.3× 38 1.1× 3 411
Elena Garré Sweden 14 507 1.2× 77 0.3× 37 0.5× 17 0.4× 61 1.8× 22 673
Kaixian Qian China 11 248 0.6× 66 0.2× 32 0.4× 43 1.1× 12 0.4× 22 399
Haifeng Chen China 11 187 0.5× 85 0.3× 217 3.0× 43 1.1× 91 2.7× 45 464
Zhixing Wang China 15 394 0.9× 304 1.1× 38 0.5× 10 0.3× 16 0.5× 64 586

Countries citing papers authored by Youichi Naoe

Since Specialization
Citations

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

Fields of papers citing papers by Youichi Naoe

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Youichi Naoe

This figure shows the co-authorship network connecting the top 25 collaborators of Youichi Naoe. A scholar is included among the top collaborators of Youichi Naoe 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 Youichi Naoe. Youichi Naoe is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

9 of 9 papers shown
1.
Naoe, Youichi, et al.. (2024). Neutralization sensitivity of SARS-CoV-2 Omicron variants FL.1 and GE.1 by therapeutic antibodies and XBB sera. Virology. 595. 110067–110067. 2 indexed citations
2.
Okuzaki, Yuya, Youichi Naoe, Joseph Lee, et al.. (2023). Dual CRISPR-Cas3 system for inducing multi-exon skipping in DMD patient-derived iPSCs. Stem Cell Reports. 18(9). 1753–1765. 7 indexed citations
3.
Kenjo, Eriya, Hiroyuki Hozumi, Yukimasa Makita, et al.. (2021). Low immunogenicity of LNP allows repeated administrations of CRISPR-Cas9 mRNA into skeletal muscle in mice. Nature Communications. 12(1). 7101–7101. 209 indexed citations breakdown →
4.
Naoe, Youichi, Takehiko Tosha, Satoru Nagatoishi, et al.. (2017). Structural basis for binding and transfer of heme in bacterial heme‐acquisition systems. Proteins Structure Function and Bioinformatics. 85(12). 2217–2230. 6 indexed citations
5.
Naoe, Youichi, et al.. (2016). Crystal structure of bacterial haem importer complex in the inward-facing conformation. Nature Communications. 7(1). 13411–13411. 33 indexed citations
6.
Sato, Tomomi, Yohei Miyanoiri, Mitsuhiro Takeda, et al.. (2014). Expression and purification of a GRAS domain of SLR1, the rice DELLA protein. Protein Expression and Purification. 95. 248–258. 16 indexed citations
7.
Shimada, Asako, Miyako Ueguchi‐Tanaka, Toru Nakatsu, et al.. (2008). Structural basis for gibberellin recognition by its receptor GID1. Nature. 456(7221). 520–523. 277 indexed citations
8.
Naoe, Youichi, Kyohei Arita, Hiroshi Hashimoto, et al.. (2005). Crystallization and preliminary X-ray crystallographic analysis of rat calcineurin B homologous protein 1. Acta Crystallographica Section F Structural Biology and Crystallization Communications. 61(6). 612–613. 2 indexed citations
9.
Naoe, Youichi, Kyohei Arita, Hiroshi Hashimoto, et al.. (2005). Structural Characterization of Calcineurin B Homologous Protein 1. Journal of Biological Chemistry. 280(37). 32372–32378. 21 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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