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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...
Autores principales: | , |
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2007
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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. |
format | Text |
id | pubmed-1995542 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2007 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT schlittthomas currentapproachestogeneregulatorynetworkmodelling AT brazmaalvis currentapproachestogeneregulatorynetworkmodelling |