Analyzing pharmacological intervention points: A method to calculate external stimuli to switch between steady states in regulatory networks.

Once biological systems are modeled by regulatory networks, the next step is to include external stimuli, which model the experimental possibilities to affect the activity level of certain network's nodes, in a mathematical framework. Then, this framework can be interpreted as a mathematical op...

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Main Authors: Tim Breitenbach, Chunguang Liang, Niklas Beyersdorf, Thomas Dandekar
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2019-07-01
Series:PLoS Computational Biology
Online Access:https://doi.org/10.1371/journal.pcbi.1007075
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spelling doaj-b12ce79da7244e52983c2fc441eb0d172021-04-21T15:10:44ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582019-07-01157e100707510.1371/journal.pcbi.1007075Analyzing pharmacological intervention points: A method to calculate external stimuli to switch between steady states in regulatory networks.Tim BreitenbachChunguang LiangNiklas BeyersdorfThomas DandekarOnce biological systems are modeled by regulatory networks, the next step is to include external stimuli, which model the experimental possibilities to affect the activity level of certain network's nodes, in a mathematical framework. Then, this framework can be interpreted as a mathematical optimal control framework such that optimization algorithms can be used to determine external stimuli which cause a desired switch from an initial state of the network to another final state. These external stimuli are the intervention points for the corresponding biological experiment to obtain the desired outcome of the considered experiment. In this work, the model of regulatory networks is extended to controlled regulatory networks. For this purpose, external stimuli are considered which can affect the activity of the network's nodes by activation or inhibition. A method is presented how to calculate a selection of external stimuli which causes a switch between two different steady states of a regulatory network. A software solution based on Jimena and Mathworks Matlab is provided. Furthermore, numerical examples are presented to demonstrate application and scope of the software on networks of 4 nodes, 11 nodes and 36 nodes. Moreover, we analyze the aggregation of platelets and the behavior of a basic T-helper cell protein-protein interaction network and its maturation towards Th0, Th1, Th2, Th17 and Treg cells in accordance with experimental data.https://doi.org/10.1371/journal.pcbi.1007075
collection DOAJ
language English
format Article
sources DOAJ
author Tim Breitenbach
Chunguang Liang
Niklas Beyersdorf
Thomas Dandekar
spellingShingle Tim Breitenbach
Chunguang Liang
Niklas Beyersdorf
Thomas Dandekar
Analyzing pharmacological intervention points: A method to calculate external stimuli to switch between steady states in regulatory networks.
PLoS Computational Biology
author_facet Tim Breitenbach
Chunguang Liang
Niklas Beyersdorf
Thomas Dandekar
author_sort Tim Breitenbach
title Analyzing pharmacological intervention points: A method to calculate external stimuli to switch between steady states in regulatory networks.
title_short Analyzing pharmacological intervention points: A method to calculate external stimuli to switch between steady states in regulatory networks.
title_full Analyzing pharmacological intervention points: A method to calculate external stimuli to switch between steady states in regulatory networks.
title_fullStr Analyzing pharmacological intervention points: A method to calculate external stimuli to switch between steady states in regulatory networks.
title_full_unstemmed Analyzing pharmacological intervention points: A method to calculate external stimuli to switch between steady states in regulatory networks.
title_sort analyzing pharmacological intervention points: a method to calculate external stimuli to switch between steady states in regulatory networks.
publisher Public Library of Science (PLoS)
series PLoS Computational Biology
issn 1553-734X
1553-7358
publishDate 2019-07-01
description Once biological systems are modeled by regulatory networks, the next step is to include external stimuli, which model the experimental possibilities to affect the activity level of certain network's nodes, in a mathematical framework. Then, this framework can be interpreted as a mathematical optimal control framework such that optimization algorithms can be used to determine external stimuli which cause a desired switch from an initial state of the network to another final state. These external stimuli are the intervention points for the corresponding biological experiment to obtain the desired outcome of the considered experiment. In this work, the model of regulatory networks is extended to controlled regulatory networks. For this purpose, external stimuli are considered which can affect the activity of the network's nodes by activation or inhibition. A method is presented how to calculate a selection of external stimuli which causes a switch between two different steady states of a regulatory network. A software solution based on Jimena and Mathworks Matlab is provided. Furthermore, numerical examples are presented to demonstrate application and scope of the software on networks of 4 nodes, 11 nodes and 36 nodes. Moreover, we analyze the aggregation of platelets and the behavior of a basic T-helper cell protein-protein interaction network and its maturation towards Th0, Th1, Th2, Th17 and Treg cells in accordance with experimental data.
url https://doi.org/10.1371/journal.pcbi.1007075
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