Bioinformatics utilities, web resources and integrative strategies for the analysis of miRNA regulatory networks

MicroRNAs (miRNAs) are negative posttranscriptional regulators of gene expression, generated from the transcription and processing of specific genomic loci. In animal cells, miRNA action is exerted by their partial complementarity with the 3'-UTR of messenger RNAs and the recruitment of specific regulatory proteins that form the RNA-induced silencing complex. The regulatory action of a single miRNA could be inferred by the prediction of its mRNA targets using specific computational methods. However, complex biological processes are often controlled by a combination of several miRNAs, and the proper understanding of this regulation requires a more integrative analysis that needs to follow the principles of synthetic biology. In this chapter, we will discuss the principles of miRNA target recognition and the computational approaches for analyzing miRNA-centered regulatory networks starting from experimental data. We will also propose a workflow for the computational analysis of miRNA function using a combination of multiple target prediction algorithms together with a graphical representation of the results. This workflow is based on information layers (miRNA targets, protein-protein interaction networks, and functional clustering) to produce an integrative landscape and will be illustrated with an analysis of the miRNA functions observed in a cohort of lung adenocarcinoma patients.