mSGR is a Bayesian framework that infers spatially varying gene regulatory networks from multi-resolution hierarchical spatial transcriptomics data using Gaussian process priors and variational Bayes inference.
Notably, whena gp = 0, the modified squared exponential kernel becomes a standard exponential kernel
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
stat.AP 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Multi-resolution Spatial Graphical Regression Models for Hierarchical Spatial Transcriptomics Data
mSGR is a Bayesian framework that infers spatially varying gene regulatory networks from multi-resolution hierarchical spatial transcriptomics data using Gaussian process priors and variational Bayes inference.