Methodology article
MMpred: functional miRNA – mRNA interaction analyses by miRNA expression prediction
1 Cranfield Health, Cranfield University, Vincent Building, Cranfield, UK
2 Computational Biology, GlaxoSmithKline Medicine Research Centre, Gunnels Wood Road, Stevenage, UK
BMC Genomics 2012, 13:620 doi:10.1186/1471-2164-13-620
Published: 14 November 2012Additional files
Additional file 1:
Summary of all miRNA datasets performed on popular platforms in GEO (represented by at least 25 arrays, data from July 2011). Paired datasets are marked in green with mRNA array platform and number of samples stated). Description and remarks: All the data have been derived from NCBI Gene Expression Omnibus (http://www.ncbi.nlm.nih.gov/geo/). The newest and most advanced, 3rd version of Agilent Human miRNA is represented only by 49 samples, gathered in 5 datasets. The older Agilent array (version 2.0, capable of measuring 723 microRNAs), listed currently as most popular global miRNA expression test in GEO is represented only by 17 datasets containing 539 samples. Among 10 major miRNA microarray platforms available in GEO (those platforms are represented by more than 25 arrays) only 23 experiments have been identified as paired miRNA-mRNA. The vast majority of those assays concern large cancer tissue expression studies, so the chance of finding a dataset on different biological subject is relatively low.
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Additional file 2:
The complete mapping table in CSV format. Filtered for sense intronic transcripts only.
Format: CSV Size: 484KB Download file
Additional file 3:
Sample pipeline outputs in HTML format (compressed file).
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Additional file 4:
Overview of the pipeline outputs (raw MMpred output for both case studies).
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Additional file 5:
The short description of analysed case studies.
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Additional file 6:
Detailed report on case study I: Toll-like 4 receptor activated by Lipopolysaccharide (LPS).
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Additional file 7:
Detailed report on case study II: Comparison of miRNA regulation in human severe blunt trauma and severe burn injury.
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Additional file 8:
Systematic validation of target prediction by the similarity of binding free energy distribution with miRecords.
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Additional file 9:
Examples of MMpred predictions supported by experimental data and mapping against current databases.
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Additional file 10:
The detailed description of software implementation in R language.
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Additional file 11:
The R implementation of the presented method: MMpred.
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