Boolean network model predicts knockout mutant phenotypes of fission yeast.

<h4>Boolean networks (or</h4>networks of switches) are extremely simple mathematical models of biochemical signaling networks. Under certain circumstances, Boolean networks, despite their simplicity, are capable of predicting dynamical activation patterns of gene regulatory networks in l...

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Autores principales:	Maria I Davidich, Stefan Bornholdt
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2013
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/298fc7e989054a4e84aa4a844b1d20cb
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spelling	oai:doaj.org-article:298fc7e989054a4e84aa4a844b1d20cb2021-11-18T08:54:37ZBoolean network model predicts knockout mutant phenotypes of fission yeast.1932-620310.1371/journal.pone.0071786https://doaj.org/article/298fc7e989054a4e84aa4a844b1d20cb2013-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/24069138/pdf/?tool=EBIhttps://doaj.org/toc/1932-6203<h4>Boolean networks (or</h4>networks of switches) are extremely simple mathematical models of biochemical signaling networks. Under certain circumstances, Boolean networks, despite their simplicity, are capable of predicting dynamical activation patterns of gene regulatory networks in living cells. For example, the temporal sequence of cell cycle activation patterns in yeasts S. pombe and S. cerevisiae are faithfully reproduced by Boolean network models. An interesting question is whether this simple model class could also predict a more complex cellular phenomenology as, for example, the cell cycle dynamics under various knockout mutants instead of the wild type dynamics, only. Here we show that a Boolean network model for the cell cycle control network of yeast S. pombe correctly predicts viability of a large number of known mutants. So far this had been left to the more detailed differential equation models of the biochemical kinetics of the yeast cell cycle network and was commonly thought to be out of reach for models as simplistic as Boolean networks. The new results support our vision that Boolean networks may complement other mathematical models in systems biology to a larger extent than expected so far, and may fill a gap where simplicity of the model and a preference for an overall dynamical blueprint of cellular regulation, instead of biochemical details, are in the focus.Maria I DavidichStefan BornholdtPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 8, Iss 9, p e71786 (2013)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Maria I Davidich Stefan Bornholdt Boolean network model predicts knockout mutant phenotypes of fission yeast.
description	<h4>Boolean networks (or</h4>networks of switches) are extremely simple mathematical models of biochemical signaling networks. Under certain circumstances, Boolean networks, despite their simplicity, are capable of predicting dynamical activation patterns of gene regulatory networks in living cells. For example, the temporal sequence of cell cycle activation patterns in yeasts S. pombe and S. cerevisiae are faithfully reproduced by Boolean network models. An interesting question is whether this simple model class could also predict a more complex cellular phenomenology as, for example, the cell cycle dynamics under various knockout mutants instead of the wild type dynamics, only. Here we show that a Boolean network model for the cell cycle control network of yeast S. pombe correctly predicts viability of a large number of known mutants. So far this had been left to the more detailed differential equation models of the biochemical kinetics of the yeast cell cycle network and was commonly thought to be out of reach for models as simplistic as Boolean networks. The new results support our vision that Boolean networks may complement other mathematical models in systems biology to a larger extent than expected so far, and may fill a gap where simplicity of the model and a preference for an overall dynamical blueprint of cellular regulation, instead of biochemical details, are in the focus.
format	article
author	Maria I Davidich Stefan Bornholdt
author_facet	Maria I Davidich Stefan Bornholdt
author_sort	Maria I Davidich
title	Boolean network model predicts knockout mutant phenotypes of fission yeast.
title_short	Boolean network model predicts knockout mutant phenotypes of fission yeast.
title_full	Boolean network model predicts knockout mutant phenotypes of fission yeast.
title_fullStr	Boolean network model predicts knockout mutant phenotypes of fission yeast.
title_full_unstemmed	Boolean network model predicts knockout mutant phenotypes of fission yeast.
title_sort	boolean network model predicts knockout mutant phenotypes of fission yeast.
publisher	Public Library of Science (PLoS)
publishDate	2013
url	https://doaj.org/article/298fc7e989054a4e84aa4a844b1d20cb
work_keys_str_mv	AT mariaidavidich booleannetworkmodelpredictsknockoutmutantphenotypesoffissionyeast AT stefanbornholdt booleannetworkmodelpredictsknockoutmutantphenotypesoffissionyeast
_version_	1718421131195580416

Boolean network model predicts knockout mutant phenotypes of fission yeast.

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