MetNet contains functionality to infer metabolic network topologies from quantitative data and highresolution mass/charge information. Using statistical models (including correlation, mutual information, regression and Bayes statistics) and quantitative data (intensity values of features) adjacency matrices are inferred that can be combined to a consensus matrix. Mass differences calculated between mass/charge values of features will be matched against a data frame of supplied mass/charge differences referring to transformations of enzymatic activities. In a third step, the two levels of information are combined to form a adjacency matrix inferred from both quantitative and structure information.
Package details 


Bioconductor views  ImmunoOncology MassSpectrometry Metabolomics Network Regression 
Maintainer  
License  GPL (>= 3) 
Version  1.9.5 
Package repository  View on GitHub 
Installation 
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