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Influence of the experimental design of gene expression studies on the inference of gene regulatory networks: environmental factors

The inference of gene regulatory networks gained within recent years a considerable interest in the biology and biomedical community. The purpose of this paper is to investigate the influence that environmental conditions can exhibit on the inference performance of network inference algorithms. Spec...

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Autor principal: Emmert-Streib, Frank
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3628739/
https://www.ncbi.nlm.nih.gov/pubmed/23638344
http://dx.doi.org/10.7717/peerj.10
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author Emmert-Streib, Frank
author_facet Emmert-Streib, Frank
author_sort Emmert-Streib, Frank
collection PubMed
description The inference of gene regulatory networks gained within recent years a considerable interest in the biology and biomedical community. The purpose of this paper is to investigate the influence that environmental conditions can exhibit on the inference performance of network inference algorithms. Specifically, we study five network inference methods, Aracne, BC3NET, CLR, C3NET and MRNET, and compare the results for three different conditions: (I) observational gene expression data: normal environmental condition, (II) interventional gene expression data: growth in rich media, (III) interventional gene expression data: normal environmental condition interrupted by a positive spike-in stimulation. Overall, we find that different statistical inference methods lead to comparable, but condition-specific results. Further, our results suggest that non-steady-state data enhance the inferability of regulatory networks.
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spelling pubmed-36287392013-05-01 Influence of the experimental design of gene expression studies on the inference of gene regulatory networks: environmental factors Emmert-Streib, Frank Peerj Bioinformatics The inference of gene regulatory networks gained within recent years a considerable interest in the biology and biomedical community. The purpose of this paper is to investigate the influence that environmental conditions can exhibit on the inference performance of network inference algorithms. Specifically, we study five network inference methods, Aracne, BC3NET, CLR, C3NET and MRNET, and compare the results for three different conditions: (I) observational gene expression data: normal environmental condition, (II) interventional gene expression data: growth in rich media, (III) interventional gene expression data: normal environmental condition interrupted by a positive spike-in stimulation. Overall, we find that different statistical inference methods lead to comparable, but condition-specific results. Further, our results suggest that non-steady-state data enhance the inferability of regulatory networks. PeerJ Inc. 2013-02-12 /pmc/articles/PMC3628739/ /pubmed/23638344 http://dx.doi.org/10.7717/peerj.10 Text en © 2013 Emmert-Streib http://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Bioinformatics
Emmert-Streib, Frank
Influence of the experimental design of gene expression studies on the inference of gene regulatory networks: environmental factors
title Influence of the experimental design of gene expression studies on the inference of gene regulatory networks: environmental factors
title_full Influence of the experimental design of gene expression studies on the inference of gene regulatory networks: environmental factors
title_fullStr Influence of the experimental design of gene expression studies on the inference of gene regulatory networks: environmental factors
title_full_unstemmed Influence of the experimental design of gene expression studies on the inference of gene regulatory networks: environmental factors
title_short Influence of the experimental design of gene expression studies on the inference of gene regulatory networks: environmental factors
title_sort influence of the experimental design of gene expression studies on the inference of gene regulatory networks: environmental factors
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3628739/
https://www.ncbi.nlm.nih.gov/pubmed/23638344
http://dx.doi.org/10.7717/peerj.10
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