CyTRANSFINDER: a Cytoscape 3.3 plugin for three-component (TF, gene, miRNA) signal transduction pathway construction. Issue 1 (December 2016)

• Record Type: Journal Article
• Authors: Politano, Gianfranco; Orso, Francesca; Raimo, Monica; Benso, Alfredo; Savino, Alessandro; Taverna, Daniela; Di Carlo, Stefano
• Is Part Of: BMC bioinformatics. Volume 17:Issue 1(2016)
• Page Start: 1
• Page End: 17
• Publication Date: 2016-12
• Subjects: microRNA -- Signal transduction pathways -- Data fusion -- Cytoscape -- Network analysis -- Pathway analysis -- Network modules; Bioinformatics -- Periodicals; Computational biology -- Periodicals; 570.285
• DOI: 10.1186/s12859-016-0964-2
• Languages: English
• ISSNs: 1471-2105

Abstract

Abstract Background Biological research increasingly relies on network models to study complex phenomena. Signal Transduction Pathways are molecular circuits that model how cells receive, process, and respond to information from the environment providing snapshots of the overall cell dynamics. Most of the attempts to reconstruct signal transduction pathways are limited to single regulator networks including only genes/proteins. However, networks involving a single type of regulator and neglecting transcriptional and post-transcriptional regulations mediated by transcription factors and microRNAs, respectively, may not fully reveal the complex regulatory mechanisms of a cell. We observed a lack of computational instruments supporting explorative analysis on this type of three-component signal transduction pathways. Results We have developed CyTRANSFINDER, a new Cytoscape plugin able to infer three-component signal transduction pathways based on user defined regulatory patterns and including miRNAs, TFs and genes. Since CyTRANSFINDER has been designed to support exploratory analysis, it does not rely on expression data. To show the potential of the plugin we have applied it in a study of two miRNAs that are particularly relevant in human melanoma progression, miR-146a andmiR-214 . Conclusions CyTRANSFINDER supports the reconstruction of small signal transduction pathways among groups of genes. Results obtained from its use in a real case study have been analyzed and validated through both literature data and preliminary wet-lab experiments, showing the potential of this tool when performing exploratory analysis.