Computational analysis and prediction of microRNA binding sites
Seminar Room 1, Newton Institute
MicroRNAs (miRNAs) are small 22 nucleotide RNA molecules that directly bind to the 3' Untranslated regions of protein-coding messenger RNAs. This binding event represses the target transcript rendering it unsuitable for protein production and causing its degradation. Many miRNAs have been found and a large-number of them have already been implicated in human disease and development. We have developed a number of computational approaches for predicting the target transcripts of miRNAs. One method (miRanda) is purely computational and uses a simple dynamic programming algorithm and a statistical model to identify significant binding sites. Our second approach (Sylamer) is an algorithm for scanning genome sequences for 7mer words and testing gene-expression data to identify gene sets which are significantly enriched or depleted in such 7mer words using Hypergeometric Statistics. This combined computational/experimental approach has worked extremely well for identifying candidate miRNA targets in B and T blood cells, developing Zebrafish embryos and in mouse mutants with deafness.
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