Comput Biol Chem - Ranking of microRNA target prediction scores by Pareto front analysis.

Tópicos

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Resumo

Over the past ten years, a variety of microRNA target prediction methods has been developed, and many of the methods are constantly improved and adapted to recent insights into miRNA-mRNA interactions. In a typical scenario, different methods return different rankings of putative targets, even if the ranking is reduced to selected mRNAs that are related to a specific disease or cell type. For the experimental validation it is then difficult to decide in which order to process the predicted miRNA-mRNA bindings, since each validation is a laborious task and therefore only a limited number of mRNAs can be analysed. We propose a new ranking scheme that combines ranked predictions from several methods and - unlike standard thresholding methods - utilises the concept of Pareto fronts as defined in multi-objective optimisation. In the present study, we attempt a proof of concept by applying the new ranking scheme to hsa-miR-21, hsa-miR-125b, and hsa-miR-373 and prediction scores supplied by PITA and RNAhybrid. The scores are interpreted as a two-objective optimisation problem, and the elements of the Pareto front are ranked by the STarMir score with a subsequent re-calculation of the Pareto front after removal of the top-ranked mRNA from the basic set of prediction scores. The method is evaluated on validated targets of the three miRNA, and the ranking is compared to scores from DIANA-microT and TargetScan. We observed that the new ranking method performs well and consistent, and the first validated targets are elements of Pareto fronts at a relatively early stage of the recurrent procedure, which encourages further research towards a higher-dimensional analysis of Pareto fronts.

Resumo Limpo

past ten year varieti microrna target predict method develop mani method constant improv adapt recent insight mirnamrna interact typic scenario differ method return differ rank putat target even rank reduc select mrnas relat specif diseas cell type experiment valid difficult decid order process predict mirnamrna bind sinc valid labori task therefor limit number mrnas can analys propos new rank scheme combin rank predict sever method unlik standard threshold method utilis concept pareto front defin multiobject optimis present studi attempt proof concept appli new rank scheme hsamir hsamirb hsamir predict score suppli pita rnahybrid score interpret twoobject optimis problem element pareto front rank starmir score subsequ recalcul pareto front remov toprank mrna basic set predict score method evalu valid target three mirna rank compar score dianamicrot targetscan observ new rank method perform well consist first valid target element pareto front relat earli stage recurr procedur encourag research toward higherdimension analysi pareto front

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