Takeshi Yoshimura
- Developmental Neuroscience top 1%
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- Axon Guidance and Neuronal Signaling 10
- Cell Biology top 2%
- Hippo pathway signaling and YAP/TAZ 7
- Microtubule and mitosis dynamics 4
- Molecular Biology top 5%
- Glycosylation and Glycoproteins Research 7
- Ubiquitin and proteasome pathways 3
- Neurology top 10%
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- Embedded Systems Design Techniques 5
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- VLSI and FPGA Design Techniques 4
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- Fluid Dynamics and Vibration Analysis 3
- Co-authors
- Kozo KaibuchiNariko ArimuraYoji KawanoSaeko KawabataAkira KikuchiMatthew N. RasbandHiromichi ShiratakiDaisuke Tsuboi
- Partner nations
- JapanUnited StatesRussia
In The Last Decade
Takeshi Yoshimura
60 papers receiving 2.5k citations
Hit Papers
Peers
Comparison fields: 5 of 121
- Developmental Neuroscience 415
- Cellular and Molecular Neuroscience 1.2k
- Cell Biology 759
- Molecular Biology 1.3k
- Neurology 109
Countries citing papers authored by Takeshi Yoshimura
This map shows the geographic impact of Takeshi Yoshimura'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 Takeshi Yoshimura with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Takeshi Yoshimura more than expected).
Fields of papers citing papers by Takeshi Yoshimura
This network shows the impact of papers produced by Takeshi Yoshimura. 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 Takeshi Yoshimura. The network helps show where Takeshi Yoshimura may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Takeshi Yoshimura, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2023 | 4 | |
| 3 | 2022 | 16 | |
| 4 | 2019 | 7 | |
| 5 | Refinement of Utterance Database and Concatenation of Utterances for Enhancing System Utterances in Chat-oriented Dialogue System. | 2018 | 1 |
| 6 | 2017 | 12 | |
| 7 | Random Block Background Modelling for Foreground Detection in UHD videos (マルチメディア・仮想環境基礎) | 2016 | 1 |
| 8 | 2016 | 17 | |
| 9 | 2014 | 33 | |
| 10 | 2014 | 68 | |
| 11 | 2013 | 23 | |
| 12 | 2012 | 41 | |
| 13 | 2012 | 9 | |
| 14 | 2012 | 13 | |
| 15 | 2006 | 97 | |
| 16 | 2006 | 49 | |
| 17 | [Molecular mechanisms of neuronal polarity]. | 2005 | 2 |
| 18 | 2005 | 135 | |
| 19 | 2002 | 10 | |
| 20 | Automatic Generation Of Multiple Pronunciations Based On Neural Networks And Language Statistics | 1999 | 1 |
About Takeshi Yoshimura
Takeshi Yoshimura is a scholar working on Hardware and Architecture, Cellular and Molecular Neuroscience and Cell Biology, having authored 64 papers that have together received 2.5k indexed citations. Recurring topics across this work include Axon Guidance and Neuronal Signaling (10 papers), Glycosylation and Glycoproteins Research (7 papers), Hippo pathway signaling and YAP/TAZ (7 papers), Embedded Systems Design Techniques (5 papers), Microtubule and mitosis dynamics (4 papers), VLSI and FPGA Design Techniques (4 papers), Ubiquitin and proteasome pathways (3 papers) and Fluid Dynamics and Vibration Analysis (3 papers). The work is most often cited by research in Developmental Neuroscience (415 citations), Cellular and Molecular Neuroscience (1.2k citations) and Cell Biology (759 citations). Takeshi Yoshimura has collaborated with scholars based in Japan, United States and Russia. Frequent co-authors include Kozo Kaibuchi, Nariko Arimura, Yoji Kawano, Saeko Kawabata, Akira Kikuchi, Matthew N. Rasband, Hiromichi Shirataki, Daisuke Tsuboi, Takako Kaneko‐Kawano and Yoshio Goshima. Their work appears in journals such as Cell, Journal of Biological Chemistry and Neuron.
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.