Takeshi Yoshimura
- Molecular Biology top 5%
- Cellular and Molecular Neuroscience top 1%
- Cell Biology top 2%
- Developmental Neuroscience top 1%
- Physiology top 10%
- Co-authors
- Kozo KaibuchiNariko ArimuraYoji KawanoSaeko KawabataAkira KikuchiMatthew N. RasbandHiromichi ShiratakiDaisuke Tsuboi
- Topics
- Axon Guidance and Neuronal Signaling (10 papers)Glycosylation and Glycoproteins Research (7 papers)Hippo pathway signaling and YAP/TAZ (7 papers)
- Partner nations
- JapanUnited StatesRussia
In The Last Decade
Takeshi Yoshimura
60 papers receiving 2.5k citations
Hit Papers
Peers
Comparison fields: 5 of 121
- Molecular Biology 1.3k
- Cellular and Molecular Neuroscience 1.2k
- Cell Biology 759
- Developmental Neuroscience 415
- Physiology 291
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 of co-authors of Takeshi Yoshimura
This figure shows the co-authorship network connecting the top 25 collaborators of Takeshi Yoshimura. A scholar is included among the top collaborators of Takeshi Yoshimura 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 Takeshi Yoshimura. Takeshi Yoshimura is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 4 | |
| 3 | 16 | |
| 4 | 7 | |
| 5 | Refinement of Utterance Database and Concatenation of Utterances for Enhancing System Utterances in Chat-oriented Dialogue System. | 1 |
| 6 | 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) | 1 |
| 8 | 17 | |
| 9 | 33 | |
| 10 | 68 | |
| 11 | 23 | |
| 12 | 41 | |
| 13 | 9 | |
| 14 | 13 | |
| 15 | 97 | |
| 16 | 49 | |
| 17 | [Molecular mechanisms of neuronal polarity]. | 2 |
| 18 | 135 | |
| 19 | 10 | |
| 20 | Automatic Generation Of Multiple Pronunciations Based On Neural Networks And Language Statistics | 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) and Hippo pathway signaling and YAP/TAZ (7 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.