Author

Mari Yamamoto

Kindai University

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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Microbiology· 2 Developmental Biology· 1

Signature Assays, Organisms & Methods

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Organism:mouse· 2 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Research Focus:cell type annotation· 1 Research Focus:clustering· 1 Research Focus:differential expression· 1 Approach:experimental assay· 1 Research Focus:host-pathogen & immune response· 1

Frequent Co-Authors

Akihiro InoueiD· 1 shared Asuka Kamio· 1 shared Hajime Yoshioka· 1 shared Hideo MatsudaiD· 1 shared Hideo Sato· 1 shared Hirohisa MekataiD· 1 shared Hiroki TakeuchiiD· 1 shared Hiroya YurimotoiD· 1 shared

Activity by Year

2026-2026 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 28 mutual co-author links

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1 shared paperDevelopmental Biology

Akihiro InoueORCID

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

High-titer convalescent serum from cats recovered from severe fever with thrombocytopenia syndrome protects SFTSV-infected mice

Hirohisa Mekata, Mari YAMAMOTO, Takeshi Kawaguchi, Tamaki Okabayashi

The paper shows that high-titer convalescent cat serum from SFTS-recovered cats protects SFTSV-infected mice, suggesting potential for passive immunotherapy in feline SFTS.

bioRxiv · Oct 8, 2026 · PreprintMicrobiology

Minimally invasive measurement of maternal transcripts enables predicting the developmental potential of mammalian zygotes

Akihiro Inoue, Nicole Cheung, T. Yamanouchi, Hideo Matsuda, Hajime Yoshioka, Hiroki Takeuchi, Mikiko Nishioka, Mari Yamamoto, Yubao Wei, Kazuya Houri, Hideo Sato, 郭仁龙, Asuka Kamio, Hisato Kobayashi, Tomohiro Kono, , Kei Miyamoto

The paper identifies maternal transcripts linked to zygote developmental potential and demonstrates their use in predicting blastocyst formation with high specificity.

bioRxiv · Jun 6, 2026 · PreprintDevelopmental Biology

Phenotypic diversity of yeasts curated in the 5th edition of The Yeasts: A data-driven visualization approach

Taisuke Seike, Madoka Ide, Mari Yamamoto, Hiroya Yurimoto, Kosuke Shiraishi

This study curates and visualizes phenotypic data for 1,300 yeast species from The Yeasts (5th edition), revealing metabolic and ecological diversity across yeast lineages.

bioRxiv · Feb 16, 2026 · PreprintMicrobiology