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This is the development version of ternarynet; for the stable release version, see ternarynet.

Ternary Network Estimation

Bioconductor version: Development (3.20)

Gene-regulatory 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.

Author: Matthew N. McCall <mccallm at>, Anthony Almudevar <Anthony_Alumudevar at>, David Burton <David_Burton at>, Harry Stern <harry.stern at>

Maintainer: McCall N. Matthew <mccallm at>

Citation (from within R, enter citation("ternarynet")):


To install this package, start R (version "4.4") and enter:

if (!require("BiocManager", quietly = TRUE))

# The following initializes usage of Bioc devel


For older versions of R, please refer to the appropriate Bioconductor release.


To view documentation for the version of this package installed in your system, start R and enter:

ternarynet: A Computational Bayesian Approach to Ternary Network Estimation PDF R Script
Reference Manual PDF


biocViews Bayesian, CellBiology, GraphAndNetwork, Network, Software
Version 1.49.0
In Bioconductor since BioC 2.10 (R-2.15) (12.5 years)
License GPL (>= 2)
Depends R (>= 4.0)
Imports utils, igraph, methods, graphics, stats, BiocParallel
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Suggests testthat
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Enhances Rmpi, snow
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Follow Installation instructions to use this package in your R session.

Source Package ternarynet_1.49.0.tar.gz
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macOS Binary (x86_64) ternarynet_1.49.0.tgz
macOS Binary (arm64) ternarynet_1.49.0.tgz
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