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iRafNet: Integrative Random Forest for Gene Regulatory Network Inference

Provides a flexible integrative algorithm that allows information from prior data, such as protein protein interactions and gene knock-down, to be jointly considered for gene regulatory network inference.

Version: 1.1-1
Depends: R (≥ 3.0.0)
Imports: ROCR
Published: 2016-10-26
Author: Francesca Petralia [aut, cre], Pei Wang [aut], Zhidong Tu [aut], Jialiang Yang [aut], Adele Cutler [ctb], Leo Breiman [ctb], Andy Liaw [ctb], Matthew Wiener [ctb]
Maintainer: Francesca Petralia <francesca.petralia at mssm.edu>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://www.r-project.org
NeedsCompilation: yes
CRAN checks: iRafNet results

Documentation:

Reference manual: iRafNet.pdf

Downloads:

Package source: iRafNet_1.1-1.tar.gz
Windows binaries: r-devel: iRafNet_1.1-1.zip, r-release: iRafNet_1.1-1.zip, r-oldrel: iRafNet_1.1-1.zip
macOS binaries: r-release (arm64): iRafNet_1.1-1.tgz, r-oldrel (arm64): iRafNet_1.1-1.tgz, r-release (x86_64): iRafNet_1.1-1.tgz, r-oldrel (x86_64): iRafNet_1.1-1.tgz
Old sources: iRafNet archive

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.