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Current approaches to gene regulatory network modelling

Many different approaches have been developed to model and simulate gene regulatory networks. We proposed the following categories for gene regulatory network models: network parts lists, network topology models, network control logic models, and dynamic models. Here we will describe some examples f...

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Detalles Bibliográficos
Autores principales: Schlitt, Thomas, Brazma, Alvis
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2007
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1995542/
https://www.ncbi.nlm.nih.gov/pubmed/17903290
http://dx.doi.org/10.1186/1471-2105-8-S6-S9
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author Schlitt, Thomas
Brazma, Alvis
author_facet Schlitt, Thomas
Brazma, Alvis
author_sort Schlitt, Thomas
collection PubMed
description Many different approaches have been developed to model and simulate gene regulatory networks. We proposed the following categories for gene regulatory network models: network parts lists, network topology models, network control logic models, and dynamic models. Here we will describe some examples for each of these categories. We will study the topology of gene regulatory networks in yeast in more detail, comparing a direct network derived from transcription factor binding data and an indirect network derived from genome-wide expression data in mutants. Regarding the network dynamics we briefly describe discrete and continuous approaches to network modelling, then describe a hybrid model called Finite State Linear Model and demonstrate that some simple network dynamics can be simulated in this model.
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spelling pubmed-19955422007-10-02 Current approaches to gene regulatory network modelling Schlitt, Thomas Brazma, Alvis BMC Bioinformatics Review Many different approaches have been developed to model and simulate gene regulatory networks. We proposed the following categories for gene regulatory network models: network parts lists, network topology models, network control logic models, and dynamic models. Here we will describe some examples for each of these categories. We will study the topology of gene regulatory networks in yeast in more detail, comparing a direct network derived from transcription factor binding data and an indirect network derived from genome-wide expression data in mutants. Regarding the network dynamics we briefly describe discrete and continuous approaches to network modelling, then describe a hybrid model called Finite State Linear Model and demonstrate that some simple network dynamics can be simulated in this model. BioMed Central 2007-09-27 /pmc/articles/PMC1995542/ /pubmed/17903290 http://dx.doi.org/10.1186/1471-2105-8-S6-S9 Text en Copyright © 2007 Schlitt and Brazma; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Review
Schlitt, Thomas
Brazma, Alvis
Current approaches to gene regulatory network modelling
title Current approaches to gene regulatory network modelling
title_full Current approaches to gene regulatory network modelling
title_fullStr Current approaches to gene regulatory network modelling
title_full_unstemmed Current approaches to gene regulatory network modelling
title_short Current approaches to gene regulatory network modelling
title_sort current approaches to gene regulatory network modelling
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1995542/
https://www.ncbi.nlm.nih.gov/pubmed/17903290
http://dx.doi.org/10.1186/1471-2105-8-S6-S9
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