Author

M. Nakazono

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

Biology Disciplines

Click to filter author papers

Plant Biology· 3

Signature Assays, Organisms & Methods

Click to filter · or open tag

Organism:plant (other)· 3 Approach:statistical model· 3 Research Focus:differential expression· 2 Assay:bulk RNA-seq· 1 Research Focus:cell type annotation· 1 Research Focus:development & morphogenesis· 1 Approach:experimental assay· 1 Research Focus:gene regulatory network inference· 1

Frequent Co-Authors

H. Takahashi· 3 shared A. Kaga· 1 shared E. O. Fukushima· 1 shared H. Iwata· 1 shared H. Kajiya-Kanegae· 1 shared H. Seki· 1 shared H. Suzuki· 1 shared H. Takanashi· 1 shared

Activity by Year

2021-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 27 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

3 shared papersPlant Biology

H. Takahashi

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Single-cell transcriptomic analysis of pea shoot development and cell-type-specific responses to boron deficiency

X. Chen, Y. Ru, H. Takahashi, M. Nakazono, S. Shabala, S. M. Smith, M. Yu

This study uses single-cell RNA sequencing to analyze pea shoot development and cell-type-specific responses to boron deficiency, revealing differential gene expression and developmental impacts.

bioRxiv · Jun 14, 2023Plant Biology

Identification of basic helix-loop-helix transcription factors that activate betulinic acid biosynthesis by RNA-sequencing of hydroponically cultured Lotus japonicus

H. Suzuki, H. Takahashi, E. O. Fukushima, M. Nakazono, T. Muranaka, H. Seki

The paper identifies LjbHLH32 and LjbHLH50 as transcription factors that activate betulinic acid biosynthesis in Lotus japonicus through RNA-sequencing and functional experiments.

bioRxiv · Nov 16, 2022 · PreprintPlant 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