This package contains a set of functions related to network inference combining genomic data and prior information extracted from biomedical literature and structured biological databases. The main function is able to generate networks using Bayesian or regressionbased inference methods; while the former is limited to < 100 of variables, the latter may infer networks with hundreds of variables. Several statistics at the edge and node levels have been implemented (edge stability, predictive ability of each node, ...) in order to help the user to focus on high quality subnetworks. Ultimately, this package is used in the 'Predictive Networks' web application developed by the DanaFarber Cancer Institute in collaboration with Entagen.
Package details 


Author  Benjamin HaibeKains, Catharina Olsen, Gianluca Bontempi, John Quackenbush 
Bioconductor views  GraphAndNetwork NetworkInference 
Maintainer  Benjamin HaibeKains <bhaibeka@jimmy.harvard.edu>, Catharina Olsen <colsen@ulb.ac.be> 
License  Artistic2.0 
Version  1.22.0 
URL  http://compbio.dfci.harvard.edu http://www.ulb.ac.be/di/mlg 
Package repository  View on Bioconductor 
Installation 
Install the latest version of this package by entering the following in R:

Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.