Abstract | ||
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BACKGROUND: MicroRNAs (miRNAs) are non-coding RNAs that regulate gene expression by binding to the messenger RNA (mRNA) of protein coding genes. They control gene expression by either inhibiting translation or inducing mRNA degradation. A number of computational techniques have been developed to identify the targets of miRNAs. In this study we used predicted miRNA-gene interactions to analyse mRNA gene expression microarray data to predict miRNAs associated with particular diseases or conditions. RESULTS: Here we combine correspondence analysis, between group analysis and co-inertia analysis (CIA) to determine which miRNAs are associated with differences in gene expression levels in microarray data sets. Using a database of miRNA target predictions from TargetScan, TargetScanS, PicTar4way PicTar5way, and miRanda and combining these data with gene expression levels from sets of microarrays, this method produces a ranked list of miRNAs associated with a specified split in samples. We applied this to three different microarray datasets, a papillary thyroid carcinoma dataset, an in-house dataset of lipopolysaccharide treated mouse macrophages, and a multi-tissue dataset. In each case we were able to identified miRNAs of biological importance. CONCLUSIONS: We describe a technique to integrate gene expression data and miRNA target predictions from multiple sources. |
Year | DOI | Venue |
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2010 | 10.1186/1471-2105-11-257 | BMC Bioinformatics |
Keywords | Field | DocType |
gene expression,bioinformatics,microarray data,micrornas,correspondence analysis,algorithms,non coding rna,microarrays,genetics,messenger rna,microrna,genomics,biochemistry | Gene knockdown,Gene silencing,Biology,Post-transcriptional regulation,Gene expression,Gene product,Regulation of gene expression,Regulator gene,Bioinformatics,Genetics,Lin-4 microRNA precursor | Journal |
Volume | Issue | ISSN |
11 | 1 | 1471-2105 |
Citations | PageRank | References |
15 | 0.90 | 10 |
Authors | ||
7 |
Name | Order | Citations | PageRank |
---|---|---|---|
Stephen F. Madden | 1 | 23 | 1.88 |
Susan B. Carpenter | 2 | 15 | 0.90 |
Ian B. Jeffery | 3 | 134 | 7.02 |
Harry Björkbacka | 4 | 15 | 0.90 |
Katherine A. Fitzgerald | 5 | 15 | 0.90 |
Luke A. O'Neill | 6 | 15 | 1.24 |
Desmond G. Higgins | 7 | 1263 | 383.91 |