lpNet-package: Network Inference Of Perturbation Data Using a Linear...

Description Details Author(s) References

Description

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.

Details

Package: lpNet
Type: Package
Version: 1.99.2
Date: 2013-01-11
License: Artistic License 2.0

Author(s)

B. Knapp, M. R. A. Matos, J. Mazur, L. Kaderali

Maintainer: bettina.knapp@helmholtz-muenchen.de

References

Bettina Knapp and Lars Kaderali, Reconstruction of cellular signal transduction networks using perturbation assays and linear programming, PLoS ONE, 2013.

Marta R. A. Matos, Network inference : extension of linear programming model for time-series data, Master's thesis, Department of Informatics, University of Minho.


lpNet documentation built on Nov. 8, 2020, 7:08 p.m.