Author

S. F. Buysse

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Plant Biology· 1

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Organism:Arabidopsis· 1 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Research Focus:cell type annotation· 1 Approach:machine learning (classical)· 1

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A. Bleich· 1 shared A. K. Steensma· 1 shared A. Lopez-Hernandez· 1 shared A. Luckie-Duque· 1 shared A. T. Hightower· 1 shared A. Y. Husbands· 1 shared B. L. Montgomery· 1 shared B. M. Webster· 1 shared

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2023-2023 · peak 1/yr

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1 shared paperPlant Biology

A. Bleich

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1 paper

Recent·Most cited

Plant BiologybioRxivAug 20, 2023

Expression-based machine learning models for predicting plant tissue identity

S. Palande, J. Arsenault, P. Basurto-Lozada…·Krishnan

The paper uses Arabidopsis gene expression data to train machine learning models for predicting tissue identity in other flowering plants, finding that gene expression signatures are more predictive than marker genes.

DOI 10.1002/aps3.11621

Arabidopsisbulk RNA-seq

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