RulNet: A Web-Oriented Platform for Regulatory Network Inference, Application to Wheat -Omics Data.

ABSTRACT: With the increasing amount of -omics data available, a particular effort has to be made to provide suitable analysis tools. A major challenge is that of unraveling the molecular regulatory networks from massive and heterogeneous datasets. Here we describe RulNet, a web-oriented platform dedicated to the inference and analysis of regulatory networks from qualitative and quantitative -omics data by means of rule discovery. Queries for rule discovery can be written in an extended form of the RQL query language, which has a syntax similar to SQL. RulNet also offers users interactive features that progressively adjust and refine the inferred networks. In this paper, we present a functional characterization of RulNet and compare inferred networks with correlation-based approaches. The performanc

SUBMITTER: Vincent J 

PROVIDER: S-EPMC4437996 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature