Naoko Takeda

119 total papers · 1.9k total citations
66 papers, 1.5k citations indexed

About

Naoko Takeda is a scholar working on Cancer Research, Pathology and Forensic Medicine and Surgery. According to data from OpenAlex, Naoko Takeda has authored 66 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Cancer Research, 17 papers in Pathology and Forensic Medicine and 13 papers in Surgery. Recurrent topics in Naoko Takeda's work include Breast Cancer Treatment Studies (19 papers), Breast Lesions and Carcinomas (16 papers) and Breast Implant and Reconstruction (7 papers). Naoko Takeda is often cited by papers focused on Breast Cancer Treatment Studies (19 papers), Breast Lesions and Carcinomas (16 papers) and Breast Implant and Reconstruction (7 papers). Naoko Takeda collaborates with scholars based in Japan, Germany and South Korea. Naoko Takeda's co-authors include Mitsuru Sasaki, Kunio Arai, Roberto M. Malaluan, Satoshi Hirose, Tadafumi Adschiri, Bernard M. Kabyemela, Shinji Kume, Hiroshi Maegawa, Shin‐ichi Araki and Masami Chin‒Kanasaki and has published in prestigious journals such as Journal of Biological Chemistry, Cell Metabolism and Biochemical and Biophysical Research Communications.

In The Last Decade

Naoko Takeda

61 papers receiving 1.4k citations

Hit Papers

Cellulose hydrolysis in s... 1998 2026 2007 2016 1998 2020 100 200 300 400 500

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Naoko Takeda 484 367 206 203 174 66 1.5k
Jian Xu 150 0.3× 743 2.0× 183 0.9× 218 1.1× 351 2.0× 46 1.7k
Xifeng Lu 297 0.6× 657 1.8× 298 1.4× 303 1.5× 137 0.8× 52 1.7k
Yanyan Liu 181 0.4× 559 1.5× 53 0.3× 173 0.9× 144 0.8× 93 1.8k
Moo‐Yeol Lee 117 0.2× 657 1.8× 97 0.5× 131 0.6× 171 1.0× 76 1.8k
Yusuf Ali 208 0.4× 542 1.5× 228 1.1× 427 2.1× 452 2.6× 56 1.8k
Xiuli Zhang 91 0.2× 649 1.8× 71 0.3× 136 0.7× 154 0.9× 79 1.8k
Jiahong Wang 90 0.2× 406 1.1× 142 0.7× 173 0.9× 109 0.6× 72 1.2k
Kaori Yasuda 260 0.5× 809 2.2× 218 1.1× 68 0.3× 48 0.3× 102 1.8k
Ling Gao 126 0.3× 637 1.7× 215 1.0× 180 0.9× 188 1.1× 85 1.7k
Xu Cao 181 0.4× 565 1.5× 32 0.2× 179 0.9× 174 1.0× 53 1.7k

Countries citing papers authored by Naoko Takeda

Since Specialization
Citations

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

Fields of papers citing papers by Naoko Takeda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Naoko Takeda

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

All Works

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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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