A miRNA target interaction filter based on Markov model

Computational methods for miRNA target prediction have already provided a large amount of potential targets, but many of them suffer from high false positive rates, therefore a post-processing filter is needed for the predicted targets. This paper proposed a statistical method based on first-order non-homogeneous Markov chain to explore the base-pairing complementarity characteristics between miRNAs and their targets. The parameters of the model were estimated by the data set of the known miRNA-mRNA duplexes. By using our model, the true miRNA:mRNA interaction pairs can be well distinguished from the permutation pairs. It showed that our method can be an efficient post-processing filter for the predicted miRNA targets.