lpNet
Linear Programming Model for Network Inference
Bioconductor version: Release (3.19)
lpNet aims at infering biological networks, in particular signaling and gene networks. For that it takes perturbation data, either steady-state or time-series, as input and generates an LP model which allows the inference of signaling networks. For parameter identification either leave-one-out cross-validation or stratified n-fold cross-validation can be used.
Author: Bettina Knapp, Marta R. A. Matos, Johanna Mazur, Lars Kaderali
Maintainer: Lars Kaderali <lars.kaderali at uni-greifswald.de>
citation("lpNet")):
Installation
To install this package, start R (version "4.4") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("lpNet")
For older versions of R, please refer to the appropriate Bioconductor release.
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("lpNet")| lpNet, network inference with a linear optimization program. | R Script | |
| Reference Manual | ||
| NEWS | Text |
Details
| biocViews | NetworkInference, Software |
| Version | 2.36.0 |
| In Bioconductor since | BioC 2.12 (R-3.0) (11.5 years) |
| License | Artistic License 2.0 |
| Depends | lpSolve, KEGGgraph |
| Imports | |
| System Requirements | |
| URL |
See More
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| Build Report | Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Source Package | lpNet_2.36.0.tar.gz |
| Windows Binary (x86_64) | lpNet_2.36.0.zip (64-bit only) |
| macOS Binary (x86_64) | lpNet_2.36.0.tgz |
| macOS Binary (arm64) | lpNet_2.36.0.tgz |
| Source Repository | git clone https://git.bioconductor.org/packages/lpNet |
| Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/lpNet |
| Bioc Package Browser | https://code.bioconductor.org/browse/lpNet/ |
| Package Short Url | https://bioconductor.org/packages/lpNet/ |
| Package Downloads Report | Download Stats |