CoSTA: unsupervised convolutional neural network learning for spatial transcriptomics analysis

CoSTA: unsupervised convolutional neural network learning for spatial transcriptomics analysis

Background: The rise of spatial transcriptomics technologies is leading to new insights about how gene regulation happens in a spatial context. Determining which genes are expressed in similar spatial patterns can reveal gene regulatory relationships across cell types in a tissue. However, many curr...

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Bibliographic Details
Main Authors: McCord, R.P (Author), Xu, Y. (Author)
Format: Article
Language:English
Published: BioMed Central Ltd 2021
Subjects:
article
cluster analysis
Cluster Analysis
Convolution
convolutional neural network
Convolutional neural network
Convolutional neural networks
Current analysis
deep learning
Deep learning
Expression patterns
Future applications
Gene clustering
gene expression
Gene expression
Gene regulatory relationships
histology
histopathology
human tissue
Matrix algebra
Neural Networks, Computer
Pixels
quantitative analysis
Quantitative measures
simulation
spatial analysis
Spatial Analysis
Spatial organization
Spatial relationships
Spatial similarity
Spatial transcriptomics
Spatial variables measurement
transcriptome
Transcriptome
transcriptomics
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