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BoolNet (version 1.44)

Generation, reconstruction, simulation and analysis of synchronous, asynchronous, and probabilistic Boolean networks

Description

Provides methods to reconstruct and generate synchronous, asynchronous, and probabilistic Boolean networks, and to analyze and visualize attractors in Boolean networks

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Version

Install

install.packages('BoolNet')

Monthly Downloads

503

Version

1.44

License

Artistic-2.0

Maintainer

Hans Kestler

Last Published

April 11th, 2011

Functions in BoolNet (1.44)

Identify attractors in a Boolean network

BoolNet-package

Analyze Boolean networks

generateRandomNKNetwork

Generate a random N-K Boolean network

Plot state tables or transition graphs of attractors

Extract a single Boolean network from a probabilistic Boolean network

print.AttractorInfo

Print attractor cycles

attractorsToLaTeX

Create LaTeX state table of attractors

print.BooleanNetwork

Print a Boolean network

reconstructNetwork

Reconstruct a Boolean network from time series of measurements

print.MarkovSimulation

Print the results of a Markov chain simulation

print.TransitionTable

Print a transition table

getPathToAttractor

Get state transitions between a state and its attractor

markovSimulation

Identify important states in probabilistic Boolean networks

loadBioTapestry

Import a network from BioTapestry

plotNetworkWiring

Plot the wiring of a Boolean network

getStateSummary

Retrieve summary information on a state

Load a Boolean network from a file

print.ProbabilisticBooleanNetwork

Print a probabilistic Boolean network

getTransitionProbabilities

Get a matrix of transitions and their probabilities in probabilistic Boolean networks

testNetworkProperties

Test properties of networks by comparing them to random networks

simplifyNetwork

Simplify the functions of a synchronous, asynchronous, or probabilistic Boolean network

Perturb a Boolean network randomly

Simulate knocked-out or over-expressed genes

Export a network to the Pajek file format

getBasinOfAttraction

Get states in basin of attraction

binarizeTimeSeries

Binarize a set of real-valued time series

Visualize state transitions and attractor basins

getTransitionTable

Retrieve the transition table of a network

plotPBNTransitions

Visualize the transitions in a probabilistic Boolean network

stateTransition

Perform a transition to the next state

yeastTimeSeries

Yeast cell cycle time series data

Mammalian cell cycle network

An artificial probabilistic Boolean network