Discovering Conserved and Diverged Patterns of MiRNA Families

Abstract

MicroRNAs (miRNAs) have been recognized as important regulators of posttranscriptional gene expression. They additionally perform crucial functions in a wide range of biological processes. Many efforts have been made to explore miRNAs, however the investigation of structural features regarding conservation and divergence through evolutionary time has been largely overlooked and underdeveloped. This chapter presents a novel association rule framework to capture interesting conserved and divergent patterns, by which to explore the regulatory roles of miRNAs, and a framework to investigate conservative positions of miRNAs using information redundancy. A structural schema is proposed to model miRNA data. Support constraints are used to control the generation of frequent itemsets. Further, a correlation measure is applied to identify strongly correlated infrequent itemsets. In addition, the single base information redundancy and the adjacent base related information redundancy are applied to measure the importance of miRNA sites. Two thresholds are employed to prune the sites without biological meaning. The derived rules and positions not only unveil important structural features of miRNAs, but also promote a comprehensive understanding of the regulatory roles of miRNAs.