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Boolean Network Model Predicts Knockout Mutant Phenotypes of Fission Yeast

Boolean networks (or: 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 ex...

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Detalles Bibliográficos
Autores principales: Davidich, Maria I., Bornholdt, Stefan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3777975/
https://www.ncbi.nlm.nih.gov/pubmed/24069138
http://dx.doi.org/10.1371/journal.pone.0071786
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author Davidich, Maria I.
Bornholdt, Stefan
author_facet Davidich, Maria I.
Bornholdt, Stefan
author_sort Davidich, Maria I.
collection PubMed
description Boolean networks (or: 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.
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spelling pubmed-37779752013-09-25 Boolean Network Model Predicts Knockout Mutant Phenotypes of Fission Yeast Davidich, Maria I. Bornholdt, Stefan PLoS One Research Article Boolean networks (or: 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. Public Library of Science 2013-09-19 /pmc/articles/PMC3777975/ /pubmed/24069138 http://dx.doi.org/10.1371/journal.pone.0071786 Text en © 2013 Davidich, Bornholdt http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Davidich, Maria I.
Bornholdt, Stefan
Boolean Network Model Predicts Knockout Mutant Phenotypes of Fission Yeast
title 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_short Boolean Network Model Predicts Knockout Mutant Phenotypes of Fission Yeast
title_sort boolean network model predicts knockout mutant phenotypes of fission yeast
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3777975/
https://www.ncbi.nlm.nih.gov/pubmed/24069138
http://dx.doi.org/10.1371/journal.pone.0071786
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