New research article „regNet: An R package for network-based propagation of gene expression alterations“ in Bioinformatics

In collaboration with the lab of Andreas Beyer (CECAD, University of Cologne), Michael Seifert published the research article „regNet: An R package for network-based propagation of gene expression alterations“ in Bioinformatics.

regNet utilizes gene expression and copy number data to learn regulatory networks for the quantification of potential impacts of individual gene expression alterations on user-defined target genes via network propagation.

In this publication, the value of regNet was demonstrated in two case studies: (i) the identification of putative major regulators that distinguish pilocytic from diffuse astrocytomas and (ii) the prediction of putative impacts of glioblastoma-specific gene copy number alterations on cell cycle pathway genes and patient survival.

Link to publication