Author

Cong Ma

Princeton UniversityORCID 0000-0003-4300-2754Unclaimed ORCID profile · follow to get notified of new preprints

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Cong Ma1 paper · Princeton University

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Bioinformatics· 1

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Approach:deep learning· 1 Research Focus:differential expression· 1 Research Focus:gene regulatory network inference· 1 Organism:human· 1 Research Focus:spatial domain detection· 1 Assay:spatial transcriptomics· 1 Approach:statistical model· 1

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Benjamin J. RaphaeliD· 1 shared Brian J. Arnold· 1 shared Hirak SarkariD· 1 shared Kohei SannoiD· 1 shared Sereno L. Lopez-Darwin· 1 shared Uthsav ChitraiD· 1 shared

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Benjamin J. RaphaelORCID

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1 paper

Recent·Most cited

BioinformaticsNature MethodsPeer-reviewedJan 23, 2025

Mapping the topography of spatial gene expression with interpretable deep learning

Uthsav Chitra, Brian J. Arnold, Hirak Sarkar…·Benjamin J. Raphael

This paper introduces GASTON, an interpretable deep learning method to map spatial gene expression topography, identifying gradients and domains in spatial transcriptomics data.

62 citationstop 1%

humanspatial transcriptomics

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