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GeNGe: systematic generation of gene regulatory networks

Summary: The analysis of gene regulatory networks (GRNs) is a central goal of bioinformatics highly accelerated by the advent of new experimental techniques, such as RNA interference. A battery of reverse engineering methods has been developed in recent years to reconstruct the underlying GRNs from...

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Detalles Bibliográficos
Autores principales: Hache, Hendrik, Wierling, Christoph, Lehrach, Hans, Herwig, Ralf
Formato: Texto
Lenguaje:English
Publicado: Oxford University Press 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2672627/
https://www.ncbi.nlm.nih.gov/pubmed/19251773
http://dx.doi.org/10.1093/bioinformatics/btp115
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author Hache, Hendrik
Wierling, Christoph
Lehrach, Hans
Herwig, Ralf
author_facet Hache, Hendrik
Wierling, Christoph
Lehrach, Hans
Herwig, Ralf
author_sort Hache, Hendrik
collection PubMed
description Summary: The analysis of gene regulatory networks (GRNs) is a central goal of bioinformatics highly accelerated by the advent of new experimental techniques, such as RNA interference. A battery of reverse engineering methods has been developed in recent years to reconstruct the underlying GRNs from these and other experimental data. However, the performance of the individual methods is poorly understood and validation of algorithmic performances is still missing to a large extent. To enable such systematic validation, we have developed the web application GeNGe (GEne Network GEnerator), a controlled framework for the automatic generation of GRNs. The theoretical model for a GRN is a non-linear differential equation system. Networks can be user-defined or constructed in a modular way with the option to introduce global and local network perturbations. Resulting data can be used, e.g. as benchmark data for evaluating GRN reconstruction methods or for predicting effects of perturbations as theoretical counterparts of biological experiments. Availability: Available online at http://genge.molgen.mpg.de Contact: hache@molgen.mpg.de Supplementary information: Supplementary data are available at Bioinformatics online.
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spelling pubmed-26726272009-04-29 GeNGe: systematic generation of gene regulatory networks Hache, Hendrik Wierling, Christoph Lehrach, Hans Herwig, Ralf Bioinformatics Applications Note Summary: The analysis of gene regulatory networks (GRNs) is a central goal of bioinformatics highly accelerated by the advent of new experimental techniques, such as RNA interference. A battery of reverse engineering methods has been developed in recent years to reconstruct the underlying GRNs from these and other experimental data. However, the performance of the individual methods is poorly understood and validation of algorithmic performances is still missing to a large extent. To enable such systematic validation, we have developed the web application GeNGe (GEne Network GEnerator), a controlled framework for the automatic generation of GRNs. The theoretical model for a GRN is a non-linear differential equation system. Networks can be user-defined or constructed in a modular way with the option to introduce global and local network perturbations. Resulting data can be used, e.g. as benchmark data for evaluating GRN reconstruction methods or for predicting effects of perturbations as theoretical counterparts of biological experiments. Availability: Available online at http://genge.molgen.mpg.de Contact: hache@molgen.mpg.de Supplementary information: Supplementary data are available at Bioinformatics online. Oxford University Press 2009-05-01 2009-02-27 /pmc/articles/PMC2672627/ /pubmed/19251773 http://dx.doi.org/10.1093/bioinformatics/btp115 Text en © 2009 The Author(s) http://creativecommons.org/licenses/by-nc/2.0/uk/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Applications Note
Hache, Hendrik
Wierling, Christoph
Lehrach, Hans
Herwig, Ralf
GeNGe: systematic generation of gene regulatory networks
title GeNGe: systematic generation of gene regulatory networks
title_full GeNGe: systematic generation of gene regulatory networks
title_fullStr GeNGe: systematic generation of gene regulatory networks
title_full_unstemmed GeNGe: systematic generation of gene regulatory networks
title_short GeNGe: systematic generation of gene regulatory networks
title_sort genge: systematic generation of gene regulatory networks
topic Applications Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2672627/
https://www.ncbi.nlm.nih.gov/pubmed/19251773
http://dx.doi.org/10.1093/bioinformatics/btp115
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