Author

Jinfeng Shao

National Institutes of HealthORCID 0000-0001-7227-6776Unclaimed ORCID profile · follow to get notified of new preprints

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Bioinformatics· 1

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Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Approach:machine learning (classical)· 1

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Yan W. AsmanniD· 1 shared Yongbing Zhao· 1 shared

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2022-2022 · peak 1/yr

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1 shared paperBioinformatics

Yan W. AsmannORCID

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1 paper

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BioinformaticsbioRxivPreprintFeb 18, 2022

Assessment and Optimization of the Interpretability of Machine Learning Models Applied to Transcriptomic Data

Yongbing Zhao, Jinfeng Shao, Yan W. Asmann

This study evaluates and optimizes the interpretability of machine learning models applied to transcriptomic data by assessing explainers on MLP and CNN architectures and identifying tissue-specific genes.

DOI 10.1101/2022.02.18.481077

bulk RNA-seqmachine learning (classical)

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