Author

Chioko Nagao

Institute for Protein Research, The University of OsakaORCID 0000-0002-7721-0642Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Neuroscience· 2 Bioinformatics· 1

Signature Assays, Organisms & Methods

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Approach:experimental assay· 2 Organism:human· 2 Research Focus:cell type annotation· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Organism:Drosophila· 1 Assay:protein sequence· 1 Assay:proteomics· 1

Frequent Co-Authors

Kenji MizuguchiiD· 3 shared Kazuma MurakamiiD· 2 shared Thi Hong Van NguyeniD· 2 shared Esha ChawlaiD· 1 shared Gal BitaniD· 1 shared Hidehito TochioiD· 1 shared Kenjiro OnoiD· 1 shared Kosuke HashimotoiD· 1 shared

Activity by Year

2023-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 27 mutual co-author links

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3 shared papersNeuroscience

Kenji MizuguchiORCID

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3 papers

Recent·Most cited

NeuroscienceNature CommunicationsPeer-reviewedJul 15, 2026

Development of an RNA Aptamer as a Therapeutic Agent for Synucleinopathies

Kazuma Murakami, Thi Hong Van Nguyen, Leo Tsuda…·Gal Bitan

This paper develops an RNA aptamer, 1R6, that targets synuclein and shows therapeutic potential in synucleinopathies by inhibiting aggregation and promoting disaggregation.

DOI 10.1038/s41467-026-75209-z

Drosophilaexperimental assay

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NeurosciencebioRxivPreprintJul 9, 2025

Proteomic and in silico dissection of MetaAggregates in amyotrophic lateral sclerosis brains

Kazuma Murakami, Thi Hong Van Nguyen, Nobuko Fujita…·Kenjiro Ono

The paper identifies molecular components of ALS-associated MetaAggregates using proteomic and in silico methods, revealing 79 candidate proteins and their potential roles in RNA processing and aggregation.

DOI 10.1101/2025.07.09.663594

humanproteomics

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BioinformaticsFrontiers in BioinformaticsPeer-reviewedDec 18, 2023

An attention network for predicting T cell receptor-peptide binding can associate attention with interpretable protein structural properties

Kyohei Koyama, Kosuke Hashimoto, Chioko Nagao, Kenji Mizuguchi

This paper develops a Transformer-based model to predict TCR-peptide binding using amino acid sequences and associates attention weights with structural properties.

15 citations

humanprotein sequence

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