Author

Nobuko Irie

Joint Research Center for Human Retrovirus Infection, Kumamoto 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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Immunology· 2 Systems Biology· 1

Signature Assays, Organisms & Methods

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Organism:mouse· 3 Research Focus:cell type annotation· 2 Approach:deep learning· 2 Assay:scRNA-seq· 2 Approach:statistical model· 2 Research Focus:trajectory inference· 2 Research Focus:benchmarking· 1 Approach:contrastive learning· 1

Frequent Co-Authors

Masahiro OnoiD· 3 shared Yorifumi SatouiD· 3 shared Omnia RedaiD· 2 shared Alan A. MelcheriD· 1 shared Il‐mi OkazakiiD· 1 shared Jehanne HassaniD· 1 shared Kevin Joseph HarringtoniD· 1 shared Kimi ArakiiD· 1 shared

Activity by Year

2025-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 38 mutual co-author links

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3 shared papersImmunology

Masahiro OnoORCID

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3 papers

Recent·Most cited

Canonical Analysis of Fluorescent Timer-Anchored Transcriptomes Resolves Joint Temporal and Developmental Progression

Nobuko Irie, Omnia Reda, Yorifumi Satou, Masahiro Ono

The paper introduces mCanonicalTockySeq, a framework that integrates temporal and developmental progression using fluorescent timer data, showing it can map human thymic cells to a mouse reference and correlate temporal coordinates with age.

bioRxiv · Mar 18, 2026 · PreprintSystems Biology

Temporal Mechanisms of T-Cell Fate Decisions under Immune Checkpoint Blockade Resolved by CanonicalTockySeq

Jehanne Hassan, Omnia Reda, Nobuko Irie, Malin Pedersen, Shane Foo, Lizzie Appleton, Il‐mi Okazaki, Taku Okazaki, Yorifumi Satou, Kevin Joseph Harrington, Alan A. Melcher, Masahiro Ono

This paper introduces CanonicalTockySeq to analyze T-cell fate decisions over time in immunotherapy, showing that effective treatment correlates with reduced antigen engagement and exhaustion signaling.

bioRxiv · Mar 12, 2026 · PreprintImmunology

Machine Learning-Assisted Decoding of Temporal Transcriptional Dynamics via Fluorescent Timer

Nobuko Irie, Naoki Takeda, Yorifumi Satou, Kimi Araki, Masahiro Ono

This study uses CRISPR, Tocky, and machine learning to analyze Foxp3 transcription dynamics in mice, revealing CNS2-dependent regulation and age-related expression patterns.

Nature Communications · Jul 1, 2025Peer-reviewedImmunology