Generegulatory network (GRN) modeling seeks to infer dependencies between genes and thereby provide insight into the regulatory relationships that exist within a cell. This package provides a computational Bayesian approach to GRN estimation from perturbation experiments using a ternary network model, in which gene expression is discretized into one of 3 states: up, unchanged, or down). The ternarynet package includes a parallel implementation of the replica exchange Monte Carlo algorithm for fitting network models, using MPI.
Package details 


Author  Matthew N. McCall <mccallm@gmail.com>, Anthony Almudevar <Anthony_Alumudevar@urmc.rochester.edu>, David Burton <David_Burton@urmc.rochester.edu>, Harry Stern <harry.stern@rochester.edu> 
Bioconductor views  Bayesian CellBiology GraphAndNetwork Network Software 
Maintainer  McCall N. Matthew <mccallm@gmail.com> 
License  GPL (>= 2) 
Version  1.35.3 
Package repository  View on GitHub 
Installation 
Install the latest version of this package by entering the following in R:

Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.