Author

Shotaro Maedera

The University of TokyoORCID 0009-0007-3447-1811Unclaimed 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· 1 Assay:bulk RNA-seq· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Research Focus:drug response / drug discovery· 1 Organism:human· 1 Assay:imaging· 1 Approach:statistical model· 1

Frequent Co-Authors

Hiroyuki KusuharaiD· 2 shared Tadahaya MizunoiD· 2 shared Setsuo Kinoshita· 1 shared Takuya ItoiD· 1 shared

Activity by Year

2018-2023 · peak 1/yr

Co-Author Collaboration Network

4 top collaborators · 6 mutual co-author links

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2 shared papersBioinformatics

Hiroyuki KusuharaORCID

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2 papers

Recent·Most cited

BioinformaticsbioRxivPreprintJul 23, 2023

Investigation of latent representation of toxicopathological images extracted by CNN model for understanding compound properties in vivo

Shotaro Maedera, Tadahaya Mizuno, Hiroyuki Kusuhara

This study evaluates using CNN-extracted latent representations from toxicopathological images to estimate compound properties in vivo, finding that layer selection significantly impacts performance.

DOI 10.1101/2023.07.23.550191

imagingdeep learning

𝕏 PostBluesky

BioinformaticsbioRxivPreprintAug 3, 2018

Orthogonal linear separation analysis: an approach to decompose the complex effect of a perturbagen

Tadahaya Mizuno, Setsuo Kinoshita, Shotaro Maedera…·Hiroyuki Kusuhara

This paper introduces OLSA, a method to decompose drug effects into basic components using transcriptome data, showing its ability to distinguish drug effects and predict novel drug activities.

DOI 10.1101/384446

humanbulk RNA-seq

𝕏 PostBluesky