Gene regulatory networks in plants: learning causality from time and perturbation

The goal of systems biology is to generate models for predicting how a system will react under untested conditions or in response to genetic perturbations. This paper discusses experimental and analytical approaches to deriving causal relationships in gene regulatory networks.

Detalles Bibliográficos
Autores principales: Krouk, Gabriel, Lingeman, Jesse, Colon, Amy Marshall, Coruzzi, Gloria, Shasha, Dennis
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Opinion
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3707030/
https://www.ncbi.nlm.nih.gov/pubmed/23805876
http://dx.doi.org/10.1186/gb-2013-14-6-123
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author Krouk, Gabriel
Lingeman, Jesse
Colon, Amy Marshall
Coruzzi, Gloria
Shasha, Dennis
author_facet Krouk, Gabriel
Lingeman, Jesse
Colon, Amy Marshall
Coruzzi, Gloria
Shasha, Dennis
author_sort Krouk, Gabriel
collection PubMed
description The goal of systems biology is to generate models for predicting how a system will react under untested conditions or in response to genetic perturbations. This paper discusses experimental and analytical approaches to deriving causal relationships in gene regulatory networks.
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spelling pubmed-37070302014-06-27 Gene regulatory networks in plants: learning causality from time and perturbation Krouk, Gabriel Lingeman, Jesse Colon, Amy Marshall Coruzzi, Gloria Shasha, Dennis Genome Biol Opinion The goal of systems biology is to generate models for predicting how a system will react under untested conditions or in response to genetic perturbations. This paper discusses experimental and analytical approaches to deriving causal relationships in gene regulatory networks. BioMed Central 2013 2013-06-27 /pmc/articles/PMC3707030/ /pubmed/23805876 http://dx.doi.org/10.1186/gb-2013-14-6-123 Text en Copyright © 2013 BioMed Central Ltd
spellingShingle Opinion
Krouk, Gabriel
Lingeman, Jesse
Colon, Amy Marshall
Coruzzi, Gloria
Shasha, Dennis
Gene regulatory networks in plants: learning causality from time and perturbation
title Gene regulatory networks in plants: learning causality from time and perturbation
title_full Gene regulatory networks in plants: learning causality from time and perturbation
title_fullStr Gene regulatory networks in plants: learning causality from time and perturbation
title_full_unstemmed Gene regulatory networks in plants: learning causality from time and perturbation
title_short Gene regulatory networks in plants: learning causality from time and perturbation
title_sort gene regulatory networks in plants: learning causality from time and perturbation
topic Opinion
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3707030/
https://www.ncbi.nlm.nih.gov/pubmed/23805876
http://dx.doi.org/10.1186/gb-2013-14-6-123
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AT coruzzigloria generegulatorynetworksinplantslearningcausalityfromtimeandperturbation
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