Comprehensive analysis of gene-environmental interactions with temporal gene expression profiles in Pseudomonas aeruginosa.
To explore gene-environment interactions, based on temporal gene expression information, we analyzed gene and treatment information intensively and inferred interaction networks accordingly. The main idea is that gene expression reflects the response of genes to environmental factors, assuming that...
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2012-01-01
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doaj-668166a397aa4d49bcddc70084bc45f52020-11-25T02:09:24ZengPublic Library of Science (PLoS)PLoS ONE1932-62032012-01-0174e3599310.1371/journal.pone.0035993Comprehensive analysis of gene-environmental interactions with temporal gene expression profiles in Pseudomonas aeruginosa.Kangmin DuanWilliam M McCulloughMichael G SuretteTony WareJiuzhou SongTo explore gene-environment interactions, based on temporal gene expression information, we analyzed gene and treatment information intensively and inferred interaction networks accordingly. The main idea is that gene expression reflects the response of genes to environmental factors, assuming that variations of gene expression occur under different conditions. Then we classified experimental conditions into several subgroups based on the similarity of temporal gene expression profiles. This procedure is useful because it allows us to combine diverse gene expression data as they become available, and, especially, allowing us to lay the regulatory relationships on a concrete biological basis. By estimating the activation points, we can visualize the gene behavior, and obtain a consensus gene activation order, and hence describe conditional regulatory relationships. The estimation of activation points and building of synthetic genetic networks may result in important new insights in the ongoing endeavor to understand the complex network of gene regulation.http://europepmc.org/articles/PMC3338772?pdf=render |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Kangmin Duan William M McCullough Michael G Surette Tony Ware Jiuzhou Song |
spellingShingle |
Kangmin Duan William M McCullough Michael G Surette Tony Ware Jiuzhou Song Comprehensive analysis of gene-environmental interactions with temporal gene expression profiles in Pseudomonas aeruginosa. PLoS ONE |
author_facet |
Kangmin Duan William M McCullough Michael G Surette Tony Ware Jiuzhou Song |
author_sort |
Kangmin Duan |
title |
Comprehensive analysis of gene-environmental interactions with temporal gene expression profiles in Pseudomonas aeruginosa. |
title_short |
Comprehensive analysis of gene-environmental interactions with temporal gene expression profiles in Pseudomonas aeruginosa. |
title_full |
Comprehensive analysis of gene-environmental interactions with temporal gene expression profiles in Pseudomonas aeruginosa. |
title_fullStr |
Comprehensive analysis of gene-environmental interactions with temporal gene expression profiles in Pseudomonas aeruginosa. |
title_full_unstemmed |
Comprehensive analysis of gene-environmental interactions with temporal gene expression profiles in Pseudomonas aeruginosa. |
title_sort |
comprehensive analysis of gene-environmental interactions with temporal gene expression profiles in pseudomonas aeruginosa. |
publisher |
Public Library of Science (PLoS) |
series |
PLoS ONE |
issn |
1932-6203 |
publishDate |
2012-01-01 |
description |
To explore gene-environment interactions, based on temporal gene expression information, we analyzed gene and treatment information intensively and inferred interaction networks accordingly. The main idea is that gene expression reflects the response of genes to environmental factors, assuming that variations of gene expression occur under different conditions. Then we classified experimental conditions into several subgroups based on the similarity of temporal gene expression profiles. This procedure is useful because it allows us to combine diverse gene expression data as they become available, and, especially, allowing us to lay the regulatory relationships on a concrete biological basis. By estimating the activation points, we can visualize the gene behavior, and obtain a consensus gene activation order, and hence describe conditional regulatory relationships. The estimation of activation points and building of synthetic genetic networks may result in important new insights in the ongoing endeavor to understand the complex network of gene regulation. |
url |
http://europepmc.org/articles/PMC3338772?pdf=render |
work_keys_str_mv |
AT kangminduan comprehensiveanalysisofgeneenvironmentalinteractionswithtemporalgeneexpressionprofilesinpseudomonasaeruginosa AT williammmccullough comprehensiveanalysisofgeneenvironmentalinteractionswithtemporalgeneexpressionprofilesinpseudomonasaeruginosa AT michaelgsurette comprehensiveanalysisofgeneenvironmentalinteractionswithtemporalgeneexpressionprofilesinpseudomonasaeruginosa AT tonyware comprehensiveanalysisofgeneenvironmentalinteractionswithtemporalgeneexpressionprofilesinpseudomonasaeruginosa AT jiuzhousong comprehensiveanalysisofgeneenvironmentalinteractionswithtemporalgeneexpressionprofilesinpseudomonasaeruginosa |
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