Genome-wide detection of sRNA targets with rNAV

The central dogma in molecular biology postulated that 'DNA makes RNA makes protein', however this dogma has been recently extended to integrate new biological activities involving small bacterial noncoding RNAs, called sRNAs. Accordingly, increasing attention has been given to these molecules over the last decade and related experimental works have shown a wide range of functional activities for these molecules. In this paper, we present rNAV (for rna NAVigator), a new tool for the visual exploration and analysis of bacterial sRNA-mediated regulatory networks. rNAV has been designed to help bioinformaticians and biologists to identify, from lists of thousands of predictions, pertinent and reasonable sRNA target candidates for carrying out experimental validations. We propose a list of dedicated algorithms and interaction tools that facilitate the exploration of such networks. These algorithms can be gathered into pipelines which can then be saved and reused over several sessions. To support exploration awareness, rNAV also provides an exploration tree view that allows to navigate through the steps of the analysis but also to select the sub-networks to visualize and compare. These comparisons are facilitated by the integration of multiple and fully linked views. We demonstrate the usefulness of our approach by a case study on Escherichia coli bacteria performed by domain experts.