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 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.
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.
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.
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.
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.
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
Wissenschaftlicher Mitarbeiter (m/w/d)
Our paper "Sparse keypoint segmentation of lung fissures: efficient geometric deep learning for abstracting volumetric images" has been published in the International Journal of Computer Assisted Radiology and Surgery. Please find electronical supplementary material here.
Our paper "Boolean network modeling and its integration with experimental read-outs: An interdiscipliary presentation using a leukemia model" has been published online first in Pathologie.
"Combined analysis of a serum mRNA/miRNA marker signature and CA 19-9 for timely and accurate diagnosis of recurrence after resection of pancreatic ductal adenocarcinoma: A prospective multicenter cohort study" has been published online first in the United European Gastroenterology Journal.
"Identifications of Similarity Metrics for Patients With Cancer: Protocol for a Scoping Review" has been published in JMIR Research Protocols.
"Recent Trends and Future Challenges in Learning from Data" has been published with Springer.
Our paper "Permutation-invariant linear classifiers" has been published in Machine Learning.
Our paper "Prediction of resistance to bevacizumab plus FOLFOX in metastatic colorectal cancer-Results of the prospective multicenter PERMAD trial" has been published in PLoS One.
Our paper "Segmentation-based cardiomegaly detection based on semi-supervised estimation of cardiothoracic ratio" has been published in Scientific Reports.
"Prospective study validating a multidimensional treatment decision score predicting the 24-month outcome in untreated patients with clinically isolated syndrome and early relapsing–remitting multiple sclerosis, the ProVal-MS study" has been published in Neurological Research and Practice.
Our paper "GatekeepR: an R shiny application for the identification of nodes with high dynamic impact in boolean networks" has been published online first in Bioinformatics.
Our paper "The Necessity of Interoperability to Uncover the Full Potential of Digital Health Devices" has been published in JMIR Medical Informatics.
"Multicentric pilot study to standardize clinical whole exome sequencing (WES) for cancer patients" has been published in npj Precision Oncology.
Our paper "AMBAR-interactive alteration annotations for molecular tumor boards" has been published in Computer Methods and Programs in Biomedicine.
"A protocol for the use of cloud-based quantum computers for logical network analysis of biological systems" has been published in STAR Protocols.
Our paper "A systems biology approach to define mechanisms, phenotypes, and drivers in PanNETs with a personalized perspective" has been published in npj systems biology and applications.
"Supporting SURgery with GEriatric Co-Management and AI (SURGE-Ahead): A study protocol for the development of a digital geriatrician" has been published in PLoS One.
"Self-Assessment of Having COVID-19 With the Corona Check Mhealth App" has been published in IEEE Journal of Biomedical and Health Informatics.
Our first quantum computing paper "Leveraging quantum computing for dynamic analyses of logical networks in systems biology" has been published in Patterns.