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• W2085762848 abstract "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." @default.
• W2085762848 created "2016-06-24" @default.
• W2085762848 creator A5029149047 @default.
• W2085762848 creator A5039134325 @default.
• W2085762848 date "2010-12-01" @default.
• W2085762848 modified "2023-09-23" @default.
• W2085762848 title "Ranking of microRNA target prediction scores by Pareto front analysis" @default.
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• W2085762848 doi "https://doi.org/10.1016/j.compbiolchem.2010.09.005" @default.
• W2085762848 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/21035401" @default.
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