Description:

Nested Effects Models (NEMs) are a class of directed graphical models originally introduced to analyze the effects of gene perturbation screens with high-dimensional phenotypes. In contrast to other graphical models like Bayesian networks or Gaussian graphical models, NEMs don't encode conditional independence statements but SUBSET RELATIONS. NEMs achieve two goals: (i) to reveal clusters of genes with highly similar phenotypic profiles, and (ii) to order (clusters of) genes according to subset relationships between phenotypes.

Changes to previous version:

Initial Announcement on mloss.org.

BibTeX Entry: Download

Corresponding Paper BibTeX Entry: Download

Supported Operating Systems: Agnostic

Data Formats: None

Tags: Bioinformatics, Structure Learning, Graph, R, High Dimensional Data, Algorithms, Graphical Models, Microarrays, Bioconductor

Archive: download here

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