Author

Shunsuke Sumi

Waseda UniversityORCID 0000-0003-1007-9472Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 2 Assay:DNA methylation· 2 Approach:statistical model· 2 Research Focus:cell type annotation· 1 Assay:CRISPR screen· 1 Approach:deep learning· 1 Research Focus:drug response / drug discovery· 1 Approach:experimental assay· 1

Frequent Co-Authors

Hirohide SaitoiD· 2 shared Michiaki HamadaiD· 2 shared Hiroki OnoiD· 1 shared Hitoshi IuchiiD· 1 shared Keisuke YamadaiD· 1 shared Knut WoltjeniD· 1 shared Koki MakinoiD· 1 shared Masahiro OnoguchiiD· 1 shared

Activity by Year

2021-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 18 mutual co-author links

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2 shared papersBioinformatics

Hirohide SaitoORCID

Mutual co-authors in cluster

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3 papers

Recent·Most cited

Alignment-free discovery of conserved RNA structures in the human genome

Shunsuke Sumi, Koki Makino, Masahiro Onoguchi, Shungo Adachi, Hirohide Saito, Michiaki Hamada

This paper introduces RLMHelix, an alignment-free method to discover conserved RNA structures in the human genome, identifying new candidates that correlate with RNA-binding protein interactions.

bioRxiv · Oct 24, 2026 · PreprintBioinformatics

Programmable mammalian translational modulators by CRISPR-associated proteins

Shunsuke Kawasaki, Hiroki Ono, Moe Hirosawa, Takeru Kuwabara, Shunsuke Sumi, Suji Lee, Knut Woltjen, Hirohide Saito

This paper develops CaRTRIDGE, a system using CRISPR-associated proteins to control mRNA translation, creating orthogonal switches and synthetic circuits in mammalian cells.

Nature Communications · Apr 19, 2023Peer-reviewedSynthetic Biology

Representation learning applications in biological sequence analysis

Hitoshi Iuchi, Taro Matsutani, Keisuke Yamada, Natsuki Iwano, Shunsuke Sumi, Shion Hosoda, Shitao Zhao, Tsukasa Fukunaga, Michiaki Hamada

This paper reviews the application of representation learning in biological sequence analysis, focusing on how embedding techniques transform sequences for functional and structural insights.

Computational and Structural Biotechnology Journal · Jan 1, 2021Peer-reviewedBioinformatics