Author

Yuki Umemori

Teijin Pharma Limited (Japan)ORCID 0000-0003-3558-9591Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 1 Approach:machine learning (classical)· 1

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Koichi Handa M. DiD· 1 shared Michiharu KageyamaiD· 1 shared Saki Yoshimura· 1 shared Takeshi IijimaiD· 1 shared

Activity by Year

2024-2024 · peak 1/yr

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1 shared paperBioinformatics

Koichi Handa M. DORCID

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1 paper

Recent·Most cited

BioinformaticsbioRxivPreprintFeb 12, 2024

Development of a novel in silico classification model to assess reactive metabolite formation in the cysteine trapping assay and investigation of important substructures

Yuki Umemori, Koichi Handa M. D, Saki Yoshimura…·Takeshi Iijima

The paper develops an in silico MPNN model to predict covalent binding risk in the cysteine trapping assay and identifies substructures associated with reactive metabolite formation.

1 citation

machine learning (classical)deep learning

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