Naoko Toki

1.4k total citations · 1 hit paper
10 papers, 1.1k citations indexed

About

Naoko Toki is a scholar working on Molecular Biology, Cancer Research and Nephrology. According to data from OpenAlex, Naoko Toki has authored 10 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 4 papers in Cancer Research and 1 paper in Nephrology. Recurrent topics in Naoko Toki's work include RNA modifications and cancer (5 papers), RNA Research and Splicing (4 papers) and Metabolomics and Mass Spectrometry Studies (2 papers). Naoko Toki is often cited by papers focused on RNA modifications and cancer (5 papers), RNA Research and Splicing (4 papers) and Metabolomics and Mass Spectrometry Studies (2 papers). Naoko Toki collaborates with scholars based in Japan, Italy and Australia. Naoko Toki's co-authors include Tomoyoshi Soga, Taira Kinoshitá, Akiyoshi Hirayama, Masaru Tomita, Hiroyasu Esumi, Masahiro Sugimoto, Kenjiro Kami, Atsushi Ochiai, Hiroko Onozuka and Norio Saito and has published in prestigious journals such as Nucleic Acids Research, Nature Communications and Cancer Research.

In The Last Decade

Naoko Toki

10 papers receiving 1.1k citations

Hit Papers

Quantitative Metabolome Profiling of Colon and Stomach Ca... 2009 2026 2014 2020 2009 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Naoko Toki Japan 7 802 411 109 107 92 10 1.1k
Daniel Tamae United States 19 532 0.7× 267 0.6× 54 0.5× 148 1.4× 41 0.4× 24 1.1k
Xin Lin China 19 668 0.8× 339 0.8× 54 0.5× 163 1.5× 34 0.4× 51 1.1k
Anilkumar Gopalakrishnapillai United States 18 747 0.9× 105 0.3× 61 0.6× 256 2.4× 70 0.8× 64 1.4k
Zhongyu Wang China 17 747 0.9× 261 0.6× 79 0.7× 151 1.4× 58 0.6× 58 1.1k
Taotao Dong China 15 616 0.8× 284 0.7× 64 0.6× 295 2.8× 65 0.7× 40 1.1k
Rajat Roy United Kingdom 15 931 1.2× 259 0.6× 48 0.4× 152 1.4× 17 0.2× 28 1.3k
Tianyu Zhu China 19 716 0.9× 276 0.7× 47 0.4× 148 1.4× 21 0.2× 82 1.1k
Kenjiro Kami Japan 16 1.4k 1.7× 815 2.0× 241 2.2× 205 1.9× 169 1.8× 23 1.9k
Karim Chahed Tunisia 21 416 0.5× 188 0.5× 73 0.7× 137 1.3× 81 0.9× 50 883
Tomoo Yoshie Japan 12 772 1.0× 296 0.7× 107 1.0× 200 1.9× 115 1.3× 19 1.1k

Countries citing papers authored by Naoko Toki

Since Specialization
Citations

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

Fields of papers citing papers by Naoko Toki

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Naoko Toki

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

All Works

10 of 10 papers shown
1.
Garreau, Marion, Julie Weidner, Russell S. Hamilton, et al.. (2024). Chemical modification patterns for microRNA therapeutic mimics: a structure-activity relationship (SAR) case-study on miR-200c. Nucleic Acids Research. 52(6). 2792–2807. 16 indexed citations
2.
3.
Toki, Naoko, Hazuki Takahashi, Matthew Valentine, et al.. (2020). SINEUP long non-coding RNA acts via PTBP1 and HNRNPK to promote translational initiation assemblies. Nucleic Acids Research. 48(20). 11626–11644. 41 indexed citations
4.
Toki, Naoko, Hazuki Takahashi, S. Zucchelli, Stefano Gustincich, & Piero Carninci. (2020). Synthetic in vitro transcribed lncRNAs (SINEUPs) with chemical modifications enhance target mRNA translation. FEBS Letters. 594(24). 4357–4369. 22 indexed citations
5.
Toki, Naoko, Yoshinori Kondo, Kenta Teruya, et al.. (2011). Site-specific isotope labeling of long RNA for structural and mechanistic studies. Nucleic Acids Research. 40(1). e7–e7. 9 indexed citations
6.
Toyohara, Takafumi, Yasutoshi Akiyama, Takehiro Suzuki, et al.. (2010). Metabolomic profiling of uremic solutes in CKD patients. Hypertension Research. 33(9). 944–952. 121 indexed citations
7.
Hirayama, Akiyoshi, Kenjiro Kami, Masahiro Sugimoto, et al.. (2009). Quantitative Metabolome Profiling of Colon and Stomach Cancer Microenvironment by Capillary Electrophoresis Time-of-Flight Mass Spectrometry. Cancer Research. 69(11). 4918–4925. 786 indexed citations breakdown →
8.
Nakamura, Hidemitsu, Makoto Hakata, Akio Miyao, et al.. (2007). A genome-wide gain-of-function analysis of rice genes using the FOX-hunting system. Plant Molecular Biology. 65(4). 357–371. 87 indexed citations
9.
Toki, Naoko, et al.. (1993). Nonlinear Inequalities Constraint Solver Combined Multiple Constraint Solvers. 8(5). 628–638. 1 indexed citations
10.
Toki, Naoko, et al.. (1979). A new determination method of antiactivator in human plasma.. PubMed. 28(3). 133–9. 2 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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