MetOncoFit identifies topological and biochemical features that are predictive of metabolic alterations in tumors using transcriptomics or copy number alterations. MetOncoFit can be used on any transcriptomics or copy number variation (CNV) dataset to compute the relative importance of a metabolic feature in predicting differential gene expression or CNV dysregulation.  MetOncoFit accounts for a broad range of metabolic attributes that have been analyzed together for the first time, including enzyme catalytic activity, gene expression levels, metabolic pathway membership, topological connectivity to biomass and media components, and the metabolic flux computed from genome-scale metabolic models.

The datasets and the MetOncoFit software package are available for download on