Author

Iori Yamahata

Institute of Science TokyoORCID 0009-0003-5725-3578Unclaimed 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:protein design· 2 Approach:deep learning· 1 Approach:machine learning (classical)· 1 Approach:optimal transport· 1 Assay:protein sequence· 1

Frequent Co-Authors

Shuto HayashiiD· 2 shared Teppei ShimamuraiD· 2 shared Hidetomo YokooiD· 1 shared Yosuke DemizuiD· 1 shared

Activity by Year

2026-2026 · peak 2/yr

Co-Author Collaboration Network

4 top collaborators · 6 mutual co-author links

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2 shared papersBioinformatics

Shuto HayashiORCID

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2 papers

Recent·Most cited

BioinformaticsbioRxivPreprintNov 13, 2026

Affinity-guided design of PDZ-binding peptides in a shared latent space

Iori Yamahata, Teppei Shimamura, Shuto Hayashi

This paper designs PDZ-binding peptides using a deep learning method that guides sequence searches in a shared latent space for different binding objectives.

DOI 10.64898/2026.11.11.765864

deep learningprotein design

𝕏 PostBluesky

BioinformaticsJournal of Chemical Information and ModelingPeer-reviewedSep 10, 2026

Closed-Loop Multi-Objective Optimization for Receptor-Selective Cell-Penetrating Peptide Design

Iori Yamahata, Hidetomo Yokoo, Yosuke Demizu…·Shuto Hayashi

The paper develops a closed-loop framework for designing receptor-selective cell-penetrating peptides using multi-objective optimization and evaluates its effectiveness through experimental validation.

DOI 10.1021/acs.jcim.6c01267

protein sequencemachine learning (classical)

𝕏 PostBluesky