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Found 3 papers, 3 papers with code
A Multivariate Poisson-Log Normal Mixture Model for Clustering Transcriptome Sequencing Data
The aim of applying mixture model-based clustering in this context is to discover groups of co-expressed genes, which can shed light on biological functions and pathways of gene products.
Methodology Quantitative Methods Computation
Finite mixtures of matrix-variate Poisson-log normal distributions for three-way count data
Matrix variate distributions offer a natural way to model three-way data and mixtures of matrix variate distributions can be used to cluster three-way data.
Methodology
Finite Mixtures of Multivariate Poisson-Log Normal Factor Analyzers for Clustering Count Data
A mixture of multivariate Poisson-log normal factor analyzers is introduced by imposing constraints on the covariance matrix, which resulted in flexible models for clustering purposes.
