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JOURNAL

Cancer Informatics

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Co-expression Network Analysis of Human lncRNAs and Cancer Genes

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Publication Date: 19 Oct 2014

Type: Review

Journal: Cancer Informatics

Citation: Cancer Informatics 2014:Suppl. 5 49-59

doi: 10.4137/CIN.S14070

Abstract

We used gene co-expression network analysis to functionally annotate long noncoding RNAs (lncRNAs) and identify their potential cancer associations. The integrated microarray data set from our previous study was used to extract the expression profiles of 1,865 lncRNAs. Known cancer genes were compiled from the Catalogue of Somatic Mutations in Cancer and UniProt databases. Co-expression analysis identified a list of previously uncharacterized lncRNAs that showed significant correlation in expression with core cancer genes. To further annotate the lncRNAs, we performed a weighted gene co-expression network analysis, which resulted in 37 co-expression modules. Three biologically interesting modules were analyzed in depth. Two of the modules showed relatively high expression in blood and brain tissues, whereas the third module was found to be downregulated in blood cells. Hub lncRNA genes and enriched functional annotation terms were identified within the modules. The results suggest the utility of this approach as well as potential roles of uncharacterized lncRNAs in leukemia and neuroblastoma.


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What Your Colleagues Say About Cancer Informatics
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Compared with other journals we considered for publishing, Cancer Informatics provided extremely rapid but quality turnaround from draft submission to a flawlessly typeset final publication.  Moreover, sharing the article is now as easy as sharing a link with no subscriptions required, and additional code and data files are equally accessible, supporting reproducible research.  Because it has published many of our references we feel confident that our target readership must follow the journal.  This is further ...
Dr Seppo Karrila (Prince of Songkla University, Thailand)
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