Author

K. Sakurai

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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Animal Behavior & Cognition· 1 Cell Biology· 1 Plant Biology· 1

Signature Assays, Organisms & Methods

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Assay:bulk RNA-seq· 2 Research Focus:cell type annotation· 2 Research Focus:differential expression· 2 Approach:statistical model· 2 Approach:experimental assay· 1 Research Focus:gene regulatory network inference· 1 Research Focus:genome assembly· 1 Organism:human· 1

Frequent Co-Authors

A. Kaga· 1 shared D. Koga· 1 shared F. Morishita· 1 shared H. Iwata· 1 shared H. Kajiya-Kanegae· 1 shared H. T. Sakurai· 1 shared H. Takahashi· 1 shared H. Takanashi· 1 shared

Activity by Year

2021-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

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1 shared paperPlant Biology

A. Kaga

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Sex-dependant differences in the ability of nicotine to modulate discrimination learning and cognitive flexibility in mice.

Y. Aomine, Y. Shimo, K. Sakurai, M. Abe, T. Macpherson, T. Ozawa, T. Hikida

This study investigates sex-dependent effects of nicotine on discrimination learning and cognitive flexibility in mice, finding differential impacts on visual discrimination and reversal learning tasks.

bioRxiv · Apr 29, 2024 · PreprintAnimal Behavior & Cognition

The cholesterol pathway of the Golgi stress response induces cell death and transcription of Golgi-related genes through metabolic dysregulation of phosphatidylinositol-4-phosphate

K. Sasaki, T. Adachi, F. Morishita, M. Toide, Y. Watanabe, H. T. Sakurai, S. Wakabayashi, S. Kusumi, T. Yamaji, K. Sakurai, D. Koga, K. Hanada, M. Yohda, H. Yoshida

bioRxiv · May 18, 2023 · PreprintCell Biology

Time-series Multi-spectral Imaging in Soybean for Improving Biomass and Genomic Prediction Accuracy

K. Sakurai, Y. Toda, H. Kajiya-Kanegae, Y. Ohmori, Y. Yamasaki, H. Takahashi, H. Takanashi, M. Tsuda, H. Tsujimoto, A. Kaga, M. Nakazono, T. Fujiwara, H. Iwata

This study uses multi-spectral imaging to predict soybean biomass by analyzing growth stages and irrigation effects on genomic and phenotypic accuracy.

bioRxiv · Sep 30, 2021 · PreprintPlant Biology