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.
Package details |
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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 | 1.47.2 |
Package repository | View on GitHub |
Installation |
Install the latest version of this package by entering the following in R:
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