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BioJazz: in silico evolution of cellular networks with unbounded complexity using rule-based modeling

Systems biologists aim to decipher the structure and dynamics of signaling and regulatory networks underpinning cellular responses; synthetic biologists can use this insight to alter existing networks or engineer de novo ones. Both tasks will benefit from an understanding of which structural and dyn...

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Detalles Bibliográficos
Autores principales: Feng, Song, Ollivier, Julien F., Swain, Peter S., Soyer, Orkun S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4627059/
https://www.ncbi.nlm.nih.gov/pubmed/26101250
http://dx.doi.org/10.1093/nar/gkv595
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author Feng, Song
Ollivier, Julien F.
Swain, Peter S.
Soyer, Orkun S.
author_facet Feng, Song
Ollivier, Julien F.
Swain, Peter S.
Soyer, Orkun S.
author_sort Feng, Song
collection PubMed
description Systems biologists aim to decipher the structure and dynamics of signaling and regulatory networks underpinning cellular responses; synthetic biologists can use this insight to alter existing networks or engineer de novo ones. Both tasks will benefit from an understanding of which structural and dynamic features of networks can emerge from evolutionary processes, through which intermediary steps these arise, and whether they embody general design principles. As natural evolution at the level of network dynamics is difficult to study, in silico evolution of network models can provide important insights. However, current tools used for in silico evolution of network dynamics are limited to ad hoc computer simulations and models. Here we introduce BioJazz, an extendable, user-friendly tool for simulating the evolution of dynamic biochemical networks. Unlike previous tools for in silico evolution, BioJazz allows for the evolution of cellular networks with unbounded complexity by combining rule-based modeling with an encoding of networks that is akin to a genome. We show that BioJazz can be used to implement biologically realistic selective pressures and allows exploration of the space of network architectures and dynamics that implement prescribed physiological functions. BioJazz is provided as an open-source tool to facilitate its further development and use. Source code and user manuals are available at: http://oss-lab.github.io/biojazz and http://osslab.lifesci.warwick.ac.uk/BioJazz.aspx.
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spelling pubmed-46270592016-03-03 BioJazz: in silico evolution of cellular networks with unbounded complexity using rule-based modeling Feng, Song Ollivier, Julien F. Swain, Peter S. Soyer, Orkun S. Nucleic Acids Res Methods Online Systems biologists aim to decipher the structure and dynamics of signaling and regulatory networks underpinning cellular responses; synthetic biologists can use this insight to alter existing networks or engineer de novo ones. Both tasks will benefit from an understanding of which structural and dynamic features of networks can emerge from evolutionary processes, through which intermediary steps these arise, and whether they embody general design principles. As natural evolution at the level of network dynamics is difficult to study, in silico evolution of network models can provide important insights. However, current tools used for in silico evolution of network dynamics are limited to ad hoc computer simulations and models. Here we introduce BioJazz, an extendable, user-friendly tool for simulating the evolution of dynamic biochemical networks. Unlike previous tools for in silico evolution, BioJazz allows for the evolution of cellular networks with unbounded complexity by combining rule-based modeling with an encoding of networks that is akin to a genome. We show that BioJazz can be used to implement biologically realistic selective pressures and allows exploration of the space of network architectures and dynamics that implement prescribed physiological functions. BioJazz is provided as an open-source tool to facilitate its further development and use. Source code and user manuals are available at: http://oss-lab.github.io/biojazz and http://osslab.lifesci.warwick.ac.uk/BioJazz.aspx. Oxford University Press 2015-10-30 2015-06-22 /pmc/articles/PMC4627059/ /pubmed/26101250 http://dx.doi.org/10.1093/nar/gkv595 Text en © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Methods Online
Feng, Song
Ollivier, Julien F.
Swain, Peter S.
Soyer, Orkun S.
BioJazz: in silico evolution of cellular networks with unbounded complexity using rule-based modeling
title BioJazz: in silico evolution of cellular networks with unbounded complexity using rule-based modeling
title_full BioJazz: in silico evolution of cellular networks with unbounded complexity using rule-based modeling
title_fullStr BioJazz: in silico evolution of cellular networks with unbounded complexity using rule-based modeling
title_full_unstemmed BioJazz: in silico evolution of cellular networks with unbounded complexity using rule-based modeling
title_short BioJazz: in silico evolution of cellular networks with unbounded complexity using rule-based modeling
title_sort biojazz: in silico evolution of cellular networks with unbounded complexity using rule-based modeling
topic Methods Online
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4627059/
https://www.ncbi.nlm.nih.gov/pubmed/26101250
http://dx.doi.org/10.1093/nar/gkv595
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