Medical Systems Biology

You are here:  Software > BoolNet

BoolNet

BoolNet is an R package for generation, reconstruction, simulation and analysis of synchronous, asynchronous and probabilistic Boolean networks. This page provides help on the installation and usage of the package. The most recent version of the package and its documentation is available from BoolNet's CRAN page.

Documentation

Documentation is included in the R package. You can get help for a command by typing ?<command> (e.g. ?getAttractors) inside R when the package is loaded.

Additionally, a step-by-step tutorial is available here.

A description of methods and algorithms can be accessed here. Furthermore, this paper discusses the attractor search in BoolNet.

Installation

The most recent source and binary packages for BoolNet are available from CRAN. The Debian Med team also maintains a package r-cran-boolnet which can be obtained from the official repositories for Debian and Ubuntu.

CRAN (all systems)

In an R console, type install.packages("BoolNet"). The package is now installed and can be loaded via library(BoolNet). The packages igraph and XML are installed automatically, as BoolNet depends on them.

Debian package (Debian/Ubuntu)

To install BoolNet from the official Debian/Ubuntu repositories, open a terminal and type

sudo apt-get install r-cran-boolnet

Please note that the Debian package may not always be the most recent version of BoolNet.

Manual installation

To install BoolNet manually, the sources (BoolNet_<version>.tar.gz) must be downloaded from CRAN and compiled. As a prerequisite, the packages igraph and XML must be installed.

  • On Mac OS, ensure that XCode Tools are installed. On Windows, you must install R-Tools for the corresponding R version. Also, make sure that R is in the search path.
  • Open a root shell (Linux/Mac OS) or the Windows command prompt, and change to the folder where the package is located.
  • Type R CMD INSTALL BoolNet_<version>.tar.gz
  • You can now start R and load the package with the command
    library(BoolNet)

Citing BoolNet

To cite the package in publications, use:

Müssel C, Hopfensitz M, Kestler HA. BoolNet - an R package for generation, reconstruction, and analysis of Boolean networks. Bioinformatics 26(10): 1378-1380, 2010. https://doi.org/10.1093/bioinformatics/btq124

Latest News

 

Our paper "Reconstructing Boolean network ensembles from single-cell data for unraveling dynamics in the aging of human hematopoietic stem cells" has been published in the Computational and Structural Biotechnology Journal.

 

The position paper "Is there a role for statistics in artificial intelligence" has been published online first in Advances in Data Analysis and Classification.

 

Our paper "Corona Health - A Study- and Sensor-Based Mobile App Platform Exploring Aspects of the COVID-19 Pandemic" has been published in the International Journal of Environmental Research and Public Health.

 

Our paper "Patient empowerment during the COVID-19 pandemic: Ensuring safe and fast communication of test results" has been published in the Journal of Medical Internet Research.

 

Our paper "Perspective on mHealth Concepts to Ensure Users’ Empowerment–From Adverse Event Tracking for COVID-19 Vaccinations to Oncological Treatment" has been published in IEEE Access.

  

Our report protocol "Digitalization of adverse event management in oncology to improve treatment outcome—A prospective study protocol" has been published in PLoS One.

 

We are happy we could contribute to Beutel et al (2021) "A prospective Feasibility Trial to Challenge Patient-Derived Pancreatic Cancer Organoids in Predicting Treatment Response" published in MDPI Cancers.