Author

Erika Usui

RIKEN BioResource Research Center

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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Bioinformatics· 3

Signature Assays, Organisms & Methods

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Research Focus:clustering· 2 Organism:human· 2 Assay:metabolomics· 2 Assay:metagenomics· 2 Organism:plant (other)· 2 Approach:statistical model· 2 Approach:Bayesian inference· 1 Research Focus:benchmarking· 1

Frequent Co-Authors

Hiroyoshi IwataiD· 3 shared Hisashi TsujimotoiD· 3 shared Kie Kumaishi· 3 shared Shungo KoboriiD· 3 shared Yasunori IchihashiiD· 3 shared Yuji YamasakiiD· 3 shared Yusuke TodaiD· 3 shared Masami Yokota HiraiiD· 2 shared

Activity by Year

2022-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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3 shared papersBioinformatics

Hiroyoshi IwataORCID

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Author profile →

3 papers

Recent·Most cited

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

Stochastic variational variable selection for high-dimensional microbiome data

Tung Dang, Kie Kumaishi, Erika Usui, Shungo Kobori, Takumi Sato, Yusuke Toda, Yuji Yamasaki, Hisashi Tsujimoto, Yasunori Ichihashi, Hiroyoshi Iwata

The paper introduces SVVS, a method for analyzing high-dimensional microbiome data, showing improved performance and faster computation compared to existing methods.

Microbiome · Dec 24, 2022Peer-reviewedBioinformatics