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  1.36.0 
URL  http://compbio.dfci.harvard.edu http://www.ulb.ac.be/di/mlg 
Package repository  View on Bioconductor 
Installation 
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