Ensemble Methods for MiRNA Target Prediction from Expression Data.

ABSTRACT:

Background

microRNAs (miRNAs) are short regulatory RNAs that are involved in several diseases, including cancers. Identifying miRNA functions is very important in understanding disease mechanisms and determining the efficacy of drugs. An increasing number of computational methods have been developed to explore miRNA functions by inferring the miRNA-mRNA regulatory relationships from data. Each of the methods is developed based on some assumptions and constraints, for instance, assuming linear relationships between variables. For such reasons, computational methods are often subject to the problem of inconsistent performance across different datasets. On the other hand, ensemble methods integrate the results from individual methods and have been proved to outperform each of their in

SUBMITTER: Le TD 

PROVIDER: S-EPMC4482624 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature