Abstract
BackgroundHigh-throughput transcriptional profiling using Next-Generation Sequencing (RNA-Seq) or microarray technology have become standard tools in molecular biology. Successful investigations of gene regulatory mechanisms from these data typically employ mathematical models of biological networks.ResultsWe have developed Wormpath, a software for molecular network discovery which operates on the genetic and physical interaction data of the Wormbase, a comprehensive resource of molecular data on Caenorhabditis elegans. We use Wormpath to show that the insulin/insulin-like growth factor signalling (IIS) pathway responds to UV-induced DNA damage during development.ConclusionsOur software provides highly facilitated access to C. elegans interaction data and is capable of identifying essential molecular networks within a list of differentially expressed genes.Electronic supplementary materialThe online version of this article (doi:10.1186/s13029-015-0034-6) contains supplementary material, which is available to authorized users.
Highlights
High-throughput transcriptional profiling using Next-Generation Sequencing (RNA-Seq) or microarray technology have become standard tools in molecular biology
To show the potential of our approach for molecular network discovery, we re-analyzed microarray data from our recent study in which we reported that genes responding to DNA damage during development are enriched in the insulin/insulin-like growth factor signalling (IIS) pathway [3]
Using iteration depth D = 1, Wormpath identifies a list of 25 molecular interaction networks significantly enriched among this set of genes (p < 0.01; Table 1)
Summary
High-throughput transcriptional profiling using Next-Generation Sequencing (RNA-Seq) or microarray technology have become standard tools in molecular biology. We describe Wormpath, a software enabling the discovery of complex networks among a set of differentially expressed genes which is optimized for use in C. elegans studies. Wormpath takes advantage of this resource to search for networks between members of a userprovided list of differentially expressed genes.
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