This repository contains the data, code and figures associated with the manuscript:
Biggs MB and Papin JA. (2016). EnsembleFBA: Improved Predictions Using Ensembles of Genome-Scale Metabolic Networks. in process.
For those just getting started, example usage code can be found in "test_eFBA()".
The "bin" folder contains the Matlab scripts to gap fill GENREs, create ensembles, and make growth or gene essentiality predictions. The code uses GENREs represented using Matlab structures in COBRA format.
The subfolder "Computational Experiments" contains Matlab scripts which reproduce the results outlined in the manuscript.
The "data" folder contains the ensembles and experimental results for each computational experiment.
The subfolder "ModelSEEDdata" contains the biochemistry data downloaded from the Model SEED and our custom scripts for parsing that data.
The subfolder "PA14" contains the gene annotation and gene essentiality data used in the computational experiments. Additionally, the draft GENRE generated by the Model SEED (the basis for the draft GENREs in the manuscript) is called "PA14_reference_genome.rxntbl".
The "figures" folder contains the R scripts for plotting our data, and the SVG files with the figures in their final layout.
Any questions can be addressed to Matt Biggs (mb3ad [at] virginia [dot] edu).