Model-free inference of direct network interactions from nonlinear collective dynamics

Model-free inference of direct network interactions from nonlinear collective dynamics

Network dynamical systems can represent the interactions involved in the collective dynamics of gene regulatory networks or metabolic circuits. Here Casadiego et al. present a method for inferring these types of interactions directly from observed time series without relying on their model.

Bibliographic Details
Main Authors: Jose Casadiego, Mor Nitzan, Sarah Hallerberg, Marc Timme
Format: Article
Language:English
Published: Nature Publishing Group 2017-12-01
Series:Nature Communications
Online Access:https://doi.org/10.1038/s41467-017-02288-4
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spelling doaj-99e6c50aea8e44d19a379dca193eff072021-05-11T07:10:03ZengNature Publishing GroupNature Communications2041-17232017-12-018111010.1038/s41467-017-02288-4Model-free inference of direct network interactions from nonlinear collective dynamicsJose Casadiego0Mor Nitzan1Sarah Hallerberg2Marc Timme3Chair for Network Dynamics, Institute for Theoretical Physics and Center for Advancing Electronics Dresden (cfaed), Technical University of DresdenRacah Institute of Physics, The Hebrew UniversityNetwork Dynamics, Max Planck Institute for Dynamics and Self-Organization (MPIDS)Chair for Network Dynamics, Institute for Theoretical Physics and Center for Advancing Electronics Dresden (cfaed), Technical University of DresdenNetwork dynamical systems can represent the interactions involved in the collective dynamics of gene regulatory networks or metabolic circuits. Here Casadiego et al. present a method for inferring these types of interactions directly from observed time series without relying on their model.https://doi.org/10.1038/s41467-017-02288-4
collection DOAJ
language English
format Article
sources DOAJ
author Jose Casadiego
Mor Nitzan
Sarah Hallerberg
Marc Timme
spellingShingle Jose Casadiego
Mor Nitzan
Sarah Hallerberg
Marc Timme
Model-free inference of direct network interactions from nonlinear collective dynamics
Nature Communications
author_facet Jose Casadiego
Mor Nitzan
Sarah Hallerberg
Marc Timme
author_sort Jose Casadiego
title Model-free inference of direct network interactions from nonlinear collective dynamics
title_short Model-free inference of direct network interactions from nonlinear collective dynamics
title_full Model-free inference of direct network interactions from nonlinear collective dynamics
title_fullStr Model-free inference of direct network interactions from nonlinear collective dynamics
title_full_unstemmed Model-free inference of direct network interactions from nonlinear collective dynamics
title_sort model-free inference of direct network interactions from nonlinear collective dynamics
publisher Nature Publishing Group
series Nature Communications
issn 2041-1723
publishDate 2017-12-01
description Network dynamical systems can represent the interactions involved in the collective dynamics of gene regulatory networks or metabolic circuits. Here Casadiego et al. present a method for inferring these types of interactions directly from observed time series without relying on their model.
url https://doi.org/10.1038/s41467-017-02288-4
work_keys_str_mv AT josecasadiego modelfreeinferenceofdirectnetworkinteractionsfromnonlinearcollectivedynamics
AT mornitzan modelfreeinferenceofdirectnetworkinteractionsfromnonlinearcollectivedynamics
AT sarahhallerberg modelfreeinferenceofdirectnetworkinteractionsfromnonlinearcollectivedynamics
AT marctimme modelfreeinferenceofdirectnetworkinteractionsfromnonlinearcollectivedynamics
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