The genome-wide gene expression profiling to predict competitive endogenous RNA network in hepatocellular cancer

To assess the potential competitive endogenous RNA (ceRNA) network in hepatocellular cancer (HCC), the lncRNA, mRNA, and microRNA microarrays were conducted on 3 pairs of HCC and paired normal liver tissue. After that, the arrays were normalized and analyzed with gene oncology (GO) and pathway analy...

Descripción completa

Detalles Bibliográficos
Autores principales: Peng, Haoran, Lu, Minqiang, Selaru, Florin M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2015
Materias:
Data in Brief
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4535840/
https://www.ncbi.nlm.nih.gov/pubmed/26484188
http://dx.doi.org/10.1016/j.gdata.2015.03.016
_version_ 1782385656392056832
author Peng, Haoran
Lu, Minqiang
Selaru, Florin M.
author_facet Peng, Haoran
Lu, Minqiang
Selaru, Florin M.
author_sort Peng, Haoran
collection PubMed
description To assess the potential competitive endogenous RNA (ceRNA) network in hepatocellular cancer (HCC), the lncRNA, mRNA, and microRNA microarrays were conducted on 3 pairs of HCC and paired normal liver tissue. After that, the arrays were normalized and analyzed with gene oncology (GO) and pathway analysis. Next, we screened out the pseudogenes and their cognate protein coding genes which are both down-regulated in HCC. Finally, the up-regulated microRNA binding sites were predicted on the most down-regulated pseudogene and its cognate protein-coding gene. All the array data were uploaded to Gene Expression Omnibus (accession number GSE64633).
format Online
Article
Text
id pubmed-4535840
institution National Center for Biotechnology Information
language English
publishDate 2015
publisher Elsevier
record_format MEDLINE/PubMed
spelling pubmed-45358402015-10-19 The genome-wide gene expression profiling to predict competitive endogenous RNA network in hepatocellular cancer Peng, Haoran Lu, Minqiang Selaru, Florin M. Genom Data Data in Brief To assess the potential competitive endogenous RNA (ceRNA) network in hepatocellular cancer (HCC), the lncRNA, mRNA, and microRNA microarrays were conducted on 3 pairs of HCC and paired normal liver tissue. After that, the arrays were normalized and analyzed with gene oncology (GO) and pathway analysis. Next, we screened out the pseudogenes and their cognate protein coding genes which are both down-regulated in HCC. Finally, the up-regulated microRNA binding sites were predicted on the most down-regulated pseudogene and its cognate protein-coding gene. All the array data were uploaded to Gene Expression Omnibus (accession number GSE64633). Elsevier 2015-04-07 /pmc/articles/PMC4535840/ /pubmed/26484188 http://dx.doi.org/10.1016/j.gdata.2015.03.016 Text en © 2015 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Data in Brief
Peng, Haoran
Lu, Minqiang
Selaru, Florin M.
The genome-wide gene expression profiling to predict competitive endogenous RNA network in hepatocellular cancer
title The genome-wide gene expression profiling to predict competitive endogenous RNA network in hepatocellular cancer
title_full The genome-wide gene expression profiling to predict competitive endogenous RNA network in hepatocellular cancer
title_fullStr The genome-wide gene expression profiling to predict competitive endogenous RNA network in hepatocellular cancer
title_full_unstemmed The genome-wide gene expression profiling to predict competitive endogenous RNA network in hepatocellular cancer
title_short The genome-wide gene expression profiling to predict competitive endogenous RNA network in hepatocellular cancer
title_sort genome-wide gene expression profiling to predict competitive endogenous rna network in hepatocellular cancer
topic Data in Brief
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4535840/
https://www.ncbi.nlm.nih.gov/pubmed/26484188
http://dx.doi.org/10.1016/j.gdata.2015.03.016
work_keys_str_mv AT penghaoran thegenomewidegeneexpressionprofilingtopredictcompetitiveendogenousrnanetworkinhepatocellularcancer
AT luminqiang thegenomewidegeneexpressionprofilingtopredictcompetitiveendogenousrnanetworkinhepatocellularcancer
AT selaruflorinm thegenomewidegeneexpressionprofilingtopredictcompetitiveendogenousrnanetworkinhepatocellularcancer
AT penghaoran genomewidegeneexpressionprofilingtopredictcompetitiveendogenousrnanetworkinhepatocellularcancer
AT luminqiang genomewidegeneexpressionprofilingtopredictcompetitiveendogenousrnanetworkinhepatocellularcancer
AT selaruflorinm genomewidegeneexpressionprofilingtopredictcompetitiveendogenousrnanetworkinhepatocellularcancer

Ejemplares similares