Author

Koyo Kuze

The University of Tokyo

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioengineering· 1 Bioinformatics· 1 Neuroscience· 1

Signature Assays, Organisms & Methods

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Assay:imaging· 3 Organism:C. elegans· 2 Research Focus:cell type annotation· 2 Approach:statistical model· 2 Research Focus:clustering· 1 Research Focus:dimensionality reduction· 1 Approach:matrix factorization· 1 Approach:microscopy & imaging analysis· 1

Frequent Co-Authors

Yu ToyoshimaiD· 3 shared Yuichi IinoiD· 3 shared Manami Kanamori· 2 shared Suzu Oe· 2 shared Takeshi IshiharaiD· 2 shared Ayumu IshijimaiD· 1 shared Chentao WeniD· 1 shared Chung-Kuan CheniD· 1 shared

Activity by Year

2022-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 35 mutual co-author links

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3 shared papersBioengineering

Yu ToyoshimaORCID

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Image-scanning light-sheet microscopy for high-speed volumetric imaging of complex biological dynamics

Yusuke Tomina, Ayumu Ishijima, Yu Toyoshima, Hikaru Shishido, Ryu Hirooka, Kazuki Mukumoto, Chentao Wen, Manami Kanamori, Koyo Kuze, Yuko Murakami, Suzu Oe, Sae Tanaka, Yusuke Yonamine, Yukinori Nishigami, Keisuke Goda, , Hideharu Mikami

The paper introduces image-scanning light-sheet microscopy to enable high-speed volumetric imaging of complex biological dynamics with improved speed while maintaining resolution and efficiency.

bioRxiv · Apr 9, 2026 · PreprintBioengineering

WormTracer: A precise method for worm posture analysis using temporal continuity

Koyo Kuze, Ukyo T. Tazawa, Karin Suwazono, Chung-Kuan Chen, Yu Toyoshima, Yuichi Iino

WormTracer improves posture analysis of C. elegans by analyzing sequences of images concurrently, generating more accurate eigenworms for posture representation.

Journal of Neuroscience Methods · Nov 30, 2025Peer-reviewedBioinformatics

Deducing ensemble dynamics and information flow from the whole-brain imaging data

Yu Toyoshima, Hirofumi Sato, Daiki Nagata, Manami Kanamori, Moon‐Sun Jang, Koyo Kuze, Suzu Oe, Takayuki Teramoto, Yuishi Iwasaki, Ryo Yoshida, Takeshi Ishihara, Yuichi Iino

The paper analyzes whole-brain imaging data of C. elegans to decompose neural dynamics and model information flow using time-delay embedding, independent component analysis, and dimensionality reduction techniques.

bioRxiv · Nov 18, 2022 · PreprintNeuroscience