Linear effects models of signaling pathways from combinatorial perturbation data
OPEN ACCESS
Loading...
Author / Producer
Date
2016-06
Publication Type
Journal Article
ETH Bibliography
yes
Citations
Altmetric
OPEN ACCESS
Data
Rights / License
Abstract
Motivation: Perturbations constitute the central means to study signaling pathways. Interrupting components of the pathway and analyzing observed effects of those interruptions can give insight into unknown connections within the signaling pathway itself, as well as the link from the pathway to the effects. Different pathway components may have different individual contributions to the measured perturbation effects, such as gene expression changes. Those effects will be observed in combination when the pathway components are perturbed. Extant approaches focus either on the reconstruction of pathway structure or on resolving how the pathway components control the downstream effects.
Results: Here, we propose a linear effects model, which can be applied to solve both these problems from combinatorial perturbation data. We use simulated data to demonstrate the accuracy of learning the pathway structure as well as estimation of the individual contributions of pathway components to the perturbation effects. The practical utility of our approach is illustrated by an application to perturbations of the mitogen-activated protein kinase pathway in Saccharomyces cerevisiae .
Permanent link
Publication status
published
External links
Editor
Book title
Journal / series
Volume
32 (12)
Pages / Article No.
Publisher
Oxford University Press
Event
Edition / version
Methods
Software
Geographic location
Date collected
Date created
Subject
Organisational unit
03790 - Beerenwinkel, Niko / Beerenwinkel, Niko
Notes
It was possible to publish this article open access thanks to a Swiss National Licence with the publisher.