Author

Yushiro Fuji

RIKEN Center for Sustainable Resource ScienceORCID 0009-0004-4465-7175Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

Click to filter author papers

Bioinformatics· 3 Plant Biology· 1

Signature Assays, Organisms & Methods

Click to filter · or open tag

Assay:metabolomics· 4 Organism:plant (other)· 4 Approach:statistical model· 3 Assay:DNA methylation· 2 Assay:multiome· 2 Approach:Bayesian inference· 1 Research Focus:benchmarking· 1 Research Focus:cell-cell communication· 1

Frequent Co-Authors

Hiroyoshi IwataiD· 4 shared Yasunori IchihashiiD· 4 shared Hisashi TsujimotoiD· 3 shared Masami Yokota HiraiiD· 3 shared Yuji YamasakiiD· 3 shared Yusuke TodaiD· 3 shared Akito KagaiD· 2 shared Erika Usui· 2 shared

Activity by Year

2025-2026 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 45 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

4 shared papersBioinformatics

Hiroyoshi IwataORCID

Mutual co-authors in cluster

Author profile →

4 papers

Recent·Most cited

Metabolome genome-wide association study reveals hierarchical and epistatic genetic control of flavonoid metabolism in soybean

Taisei Hatta, Kosuke Hamazaki, Yushiro Fuji, Yusuke Toda, Yasunori Ichihashi, Yoshihiro Ohmori, Yuji Yamasaki, Hirokazu Takahashi, Hideki Takanashi, Mai Tsuda, Hisashi Tsujimoto, Akito Kaga, Mikio Nakazono, Toru Fujiwara, Masami Yokota Hirai, Hiroyoshi Iwata

bioRxiv · Jul 24, 2026 · PreprintPlant Biology

Interpretable multi-omics machine learning reveals drought-driven shifts in plant-microbe interactions

Hayato Yoshioka, Pavla Debeljak, Soizic Prado, Yushiro Fuji, Yasunori Ichihashi, Hiroyoshi Iwata

The paper uses interpretable machine learning to analyze multi-omics data from soybean under drought stress, identifying key biomarkers and interactions influencing plant phenotypes.

Environmental Microbiome · Apr 10, 2026Peer-reviewedBioinformatics

Integration of Proxy Intermediate Omics traits into a Nonlinear Two-Step model for accurate phenotypic prediction

Hayato Yoshioka, Tristan Mary‐Huard, Julie Aubert, Yusuke Toda, Yoshihiro Ohmori, Yuji Yamasaki, Hisashi Tsujimoto, H. Takahashi, Mikio Nakazono, Hideki Takanashi, Toru Fujiwara, Mai Tsuda, Akito Kaga, Jun Inaba, Yushiro Fuji, , Hiroyoshi Iwata

The paper proposes a nonlinear two-step model integrating proxy intermediate omics traits to improve phenotypic prediction in soybean, showing better accuracy than linear models.

Theoretical and Applied Genetics · Mar 1, 2026Peer-reviewedBioinformatics

I-SVVS: Integrative stochastic variational variable selection to explore joint patterns of multi-omics microbiome data

Tung Dang, Yushiro Fuji, Kie Kumaishi, Erika Usui, Shungo Kobori, Takumi Sato, Megumi Narukawa, Yusuke Toda, Kengo Sakurai, Yuji Yamasaki, Hisashi Tsujimoto, Masami Yokota Hirai, Yasunori Ichihashi, Hiroyoshi Iwata

I-SVVS improves clustering accuracy and reduces computation time for multi-omics microbiome data across soybean, mice, and human datasets.

Briefings in Bioinformatics · May 1, 2025Peer-reviewedBioinformatics