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Papers: 10.1186/s13059-021-02313-2

https://doi.org/10.1186/s13059-021-02313-2

Schema: metric learning enables interpretable synthesis of heterogeneous single-cell modalities

Cited by: 19
Author(s): Rohit Singh, Brian Hie, Ashwin Narayan, Bonnie Berger
Published: about 4 years ago

Software Mentions 5

cran: CCA
Canonical Correlation Analysis
Papers that mentioned: 449
Very Likely Science (93)
cran: Seurat
Tools for Single Cell Genomics
Papers that mentioned: 1,512
Very Likely Science (100)
pypi: scikit-learn
A set of python modules for machine learning and data mining
Papers that mentioned: 2,431
Very Likely Science (100)
pypi: scvi-tools
Deep probabilistic analysis of single-cell omics data.
Papers that mentioned: 1
Very Likely Science (100)
pypi: SpatialDE
Spatial and Temporal DE test
Papers that mentioned: 14
Very Likely Science (100)