Author

Minoru S.H. Ko

Keio UniversityORCID 0000-0002-3530-3015Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Developmental Biology· 1 Genomics· 1

Signature Assays, Organisms & Methods

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Research Focus:gene regulatory network inference· 3 Approach:statistical model· 2 Assay:bulk RNA-seq· 1 Research Focus:cell type annotation· 1 Research Focus:cell-cell communication· 1 Assay:ChIP-seq· 1 Approach:deep learning· 1 Research Focus:differential expression· 1

Frequent Co-Authors

Tomohiko AkiyamaiD· 2 shared Alexis MorrisseyiD· 1 shared B. Franklin PughiD· 1 shared Chikara FurusawaiD· 1 shared Daniela Q. JamesiD· 1 shared Hidehisa TakahashiiD· 1 shared Hirotaka MatsumotoiD· 1 shared Hisanori KiryuiD· 1 shared

Activity by Year

2017-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 17 mutual co-author links

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2 shared papersDevelopmental Biology

Tomohiko AkiyamaORCID

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3 papers

Recent·Most cited

Functional redundancy between UTY and UTX in regulating the localization of transcription factors involved in pluripotency

Tomohiko Akiyama, Toshiya Nakahara, Saeko Sato, Kei‐ichiro Ishiguro, Masashi Yukawa, Miu Yamamoto, Hidehisa Takahashi, Minoru S.H. Ko

This study shows UTY and UTX work together to maintain gene regulation in human stem cells by supporting transcription factor localization and chromatin accessibility.

Development · Mar 30, 2026Peer-reviewedDevelopmental Biology

Joint sequence & chromatin neural networks characterize the differential abilities of Forkhead transcription factors to engage inaccessible chromatin

Sonny Arora, Jianyu Yang, Tomohiko Akiyama, Daniela Q. James, Alexis Morrissey, Thomas R. Blanda, Nitika Badjatia, William Lai, Minoru S.H. Ko, B. Franklin Pugh, Shaun Mahony

The paper investigates how sequence preferences and chromatin environments influence Fox TF binding using neural networks and mouse stem cells.

bioRxiv · Oct 6, 2023 · PreprintGenomics

SCODE: An efficient regulatory network inference algorithm from single-cell RNA-Seq during differentiation

Hirotaka Matsumoto, Hisanori Kiryu, Chikara Furusawa, Minoru S.H. Ko, Shigeru B. H. Ko, Norio Gouda, Tetsutaro Hayashi, Itoshi Nikaido

SCODE infers gene regulatory networks from single-cell RNA-Seq data during differentiation, showing improved performance and efficiency compared to existing methods.

Bioinformatics · Apr 2, 2017Peer-reviewedBioinformatics