PuSH - Publication Server of Helmholtz Zentrum München: lpNet: A linear programming approach to reconstruct signal transduction networks.

Navigation

Home

Deutsch

Research

Advanced Search

Browse by ...

... Journal

... Publication Type

... Research Data

... Publication Year

Publication overview

Support & Contact

Contact persons

Help

Data protection

Matos, M.R.* ; Knapp, B. ; Kaderali, L.*

lpNet: A linear programming approach to reconstruct signal transduction networks.

Bioinformatics 31, 3231-3233 (2015)

DOI

PMC

Open Access Gold as soon as Publ. Version/Full Text is submitted to ZB.

Abstract
Metrics
Extra information

With the widespread availability of high-throughput experimental technologies it has become possible to study hundreds to thousands of cellular factors simultaneously, such as coding- or non-coding mRNA or protein concentrations. Still, extracting information about the underlying regulatory or signaling interactions from these data remains a difficult challenge. We present a flexible approach towards network inference based on linear programming. Our method reconstructs the interactions of factors from a combination of perturbation/non-perturbation and steady-state/time-series data. We show both on simulated and real data that our methods are able to reconstruct the underlying networks fast and efficiently, thus shedding new light on biological processes and, in particular, into disease's mechanisms of action. We have implemented the approach as an R package available through bioconductor. AVAILABILITY AND IMPLEMENTATION: This R package is freely available under the Gnu Public License (GPL-3) from bioconductor.org (http://bioconductor.org/packages/release/bioc/html/lpNet.html) and is compatible with most operating systems (Windows, Linux, Mac OS) and hardware architectures. CONTACT: bettina.knapp@helmholtz-muenchen.de.

Altmetric

Additional Metrics?

[➜Log in]