Workshop in Biostatistics
|DATE:||January 21, 2016|
|TIME:||1:30 - 3:00 pm|
|LOCATION:||Medical School Office Building, Rm x303|
|TITLE:||Joint analysis of miRna and mRNA expression data
Professor, University of Navarra
microRNAs are a small non-coding RNA molecule involved in RNA silencing and post-transcriptional regulation of gene expression. microRNA bind to their target mRNAs. This link has a two-fold effect: it destabilizes the mRNA molecule and prevents the translation into a protein.
microRNA target prediction remains challenging since very few have been experimentally validated and the databases that include sequence-based predictions have large numbers of false positives. Furthermore, due to the different measuring rules used in these databases of predicted, the selection of the most reliable ones requires extensive knowledge about each algorithm. On the other hand, there are different methodologies that try to elucidate the effect of microRNAs on mRNA expression.
This talk reviews the different methodologies to integrate mRNA and miRNA expression [Muniategui et al. ] and exposes a method [Tabas et al. 2104] to measure the confidence of predicted interactions based on experimentally validated information. The output of this algorithm has been used to create a combined database with re-assigned score to each predicted interaction. The new score allow the robust combination of several databases without the effect of low-performing algorithms dragging down good-performing ones. The combined database outperforms each of the existing predictive algorithms.
A Muniategui, J Pey, F Planes, A Rubio. Joint analysis of miRNA and mRNA expression data." Briefings in Bioinformatics, 2013.
Daniel Tabas-Madrid, Ander Muniategui, Ignacio Sánchez-Caballero, Dannys Jorge Martínez-Herrera, Carlos Oscar S Sorzano, Angel Rubio and Alberto Pascual-Montano. Improving miRNA-mRNA interaction predictions." BMC Genomics, 2014; 15 Suppl 10:S2.