Author

Seiya Imoto

The University of Tokyo;Primary ORCID profile (0000-0002-2989-308X · 25 papers)Unclaimed ORCID profile · follow to get notified of new preprints

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Same name, identified by ORCID

Seiya ImotoiD25 papers · Institute of Medical Science, The University of Tokyo

Biology Disciplines

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Bioinformatics· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 1 Research Focus:gene regulatory network inference· 1 Assay:Hi-C· 1 Organism:human· 1 Assay:scRNA-seq· 1 Approach:transformer / foundation model· 1 Research Focus:variant effect prediction· 1

Frequent Co-Authors

Athanasios V. Vasilakos· 1 shared Fuyi LiiD· 1 shared Geoffrey I. WebbiD· 1 shared Jiangning SongiD· 1 shared Kai Wang· 1 shared Sihan CheniD· 1 shared Xiaoyu WangiD· 1 shared Yumeng ZhangiD· 1 shared

Activity by Year

2026-2026 · peak 1/yr

Co-Author Collaboration Network

8 top collaborators · 28 mutual co-author links

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1 shared paperBioinformatics

Athanasios V. Vasilakos

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1 paper

Recent·Most cited

Decoding Cell-type Specific Gene Regulation with CellReg3D by Integrating DNA Large Language Models and 3D Genome Structure

Xiaoyu Wang, Yumeng Zhang, Sihan Chen, Seiya Imoto, Geoffrey I. Webb, Athanasios V. Vasilakos, Fuyi Li, Kai Wang, Jiangning Song

CellReg3D integrates DNA language models and 3D genome structure to model cell-type-specific gene regulation, achieving state-of-the-art performance in predicting epigenetic marks and gene expression.

bioRxiv · Nov 4, 2026 · PreprintBioinformatics