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Detecting microRNA ...
Detecting microRNA activity from gene expression data
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Madden, Stephen F. (author)
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Carpenter, Susan B. (author)
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Jeffery, Ian B. (author)
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- Björkbacka, Harry (author)
- Lund University,Lunds universitet,Kardiovaskulär forskning - immunitet och ateroskleros,Forskargrupper vid Lunds universitet,Cardiovascular Research - Immunity and Atherosclerosis,Lund University Research Groups
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Fitzgerald, Katherine A. (author)
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O'Neill, Luke A. (author)
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Higgins, Desmond G. (author)
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(creator_code:org_t)
- 2010-05-18
- 2010
- English.
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In: BMC Bioinformatics. - : Springer Science and Business Media LLC. - 1471-2105. ; 11
- Related links:
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http://dx.doi.org/10... (free)
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https://bmcbioinform...
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https://lup.lub.lu.s...
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https://doi.org/10.1...
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Abstract
Subject headings
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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.
Subject headings
- NATURVETENSKAP -- Biologi -- Bioinformatik och systembiologi (hsv//swe)
- NATURAL SCIENCES -- Biological Sciences -- Bioinformatics and Systems Biology (hsv//eng)
Publication and Content Type
- art (subject category)
- ref (subject category)
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