Author

Koichiro Majima

Institute of Science TokyoORCID 0009-0006-5099-7680Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Research Focus:trajectory inference· 2 Research Focus:differential expression· 1 Research Focus:gene regulatory network inference· 1 Organism:human· 1 Organism:mouse· 1 Assay:scRNA-seq· 1 Assay:spatial transcriptomics· 1

Frequent Co-Authors

Teppei ShimamuraiD· 2 shared Yasuhiro KojimaiD· 2 shared Haruka HiroseiD· 1 shared Ko AbeiD· 1 shared Kodai MinouraiD· 1 shared

Activity by Year

2024-2025 · peak 1/yr

Co-Author Collaboration Network

5 top collaborators · 10 mutual co-author links

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2 shared papersBioinformatics

Teppei ShimamuraORCID

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2 papers

Recent·Most cited

BioinformaticsbioRxivPreprintNov 24, 2025

STODE: A Deep Generative Framework for Continuous Spatiotemporal Dynamics in Spatial Transcriptomics

Koichiro Majima, Yasuhiro Kojima, Teppei Shimamura

STODE reconstructs continuous spatiotemporal dynamics from discrete spatial transcriptomics data, outperforming existing methods in predicting gene expression and spatial coordinates.

DOI 10.1101/2025.11.24.690134

mousespatial transcriptomics

𝕏 PostBluesky

BioinformaticsBioinformaticsPeer-reviewedAug 20, 2024

LineageVAE: Reconstructing Historical Cell States and Transcriptomes toward Unobserved Progenitors

Koichiro Majima, Yasuhiro Kojima, Kodai Minoura…·Teppei Shimamura

LineageVAE reconstructs historical cell states and transcriptomes from scRNA-seq data to infer unobserved progenitor cell states.

12 citations

humanscRNA-seq

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