BBNI: Bayesian Inference of Boolean Genetic Networks

Implements a fully Bayesian Markov chain Monte Carlo (MCMC) approach for inferring the topology and Boolean logic transition functions of gene regulatory networks from noisy, binary time-series expression data. Network structure and Boolean rules are sampled jointly from their posterior distribution, providing principled uncertainty quantification rather than a single point estimate. Method described in Han et al. (2014) <doi:10.1371/journal.pone.0115806>.

Version:	0.1.1
Depends:	R (≥ 4.1.0)
Imports:	bitops, stats
Suggests:	knitr, rmarkdown, testthat (≥ 3.0.0)
Published:	2026-07-15
DOI:	10.32614/CRAN.package.BBNI (may not be active yet)
Author:	Anson Li [aut, cre], Shengtong Han [aut]
Maintainer:	Anson Li <liyuanrui618 at gmail.com>
BugReports:	https://github.com/anson-li8/BBNI/issues
License:	BSD_3_clause + file LICENSE
URL:	https://anson-li8.github.io/BBNI/, https://github.com/anson-li8/BBNI
NeedsCompilation:	no
Language:	en-US
Citation:	BBNI citation info
Materials:	README, NEWS
CRAN checks:	BBNI results

Documentation:

Reference manual:	BBNI.html , BBNI.pdf
Vignettes:	Bayesian Boolean Network Inference with BBNI (source)

Downloads:

Package source:	BBNI_0.1.1.tar.gz
Windows binaries:	r-devel: not available, r-release: BBNI_0.1.1.zip, r-oldrel: not available
macOS binaries:	r-release (arm64): BBNI_0.1.1.tgz, r-oldrel (arm64): BBNI_0.1.1.tgz, r-release (x86_64): BBNI_0.1.1.tgz, r-oldrel (x86_64): BBNI_0.1.1.tgz

Linking:

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