Galaxy Training Data for "Evaluating and ranking a set of pathways based on multiple metrics"

This dataset provides the inputs needed for the Galaxy Pathway Analysis workflow training tutorial (https://galaxy-synbiocad.org).

This workflow asseses the performance of predicted pathways by computing 4 criteria (target product flux, thermodynamic feasibility, pathway length, and enzyme availability). A score inform the user about the best candidate pathways to produce a compound of interest. The generated output is a collection of scored and ranked heterologous pathways.

The content of the dataset is as follows:

- A set of pathways provided in the SBML format (Systems Biology Markup Language) to be ranked, modeling heterologous pathways such as those outputted by the RetroSynthesis workflow (https://galaxy-synbiocad.org).

- The GEM (Genome-scale metabolic models) which is a formalized representation of the metabolism of the host organism (the model is E. coli iML1515), provided in the SBML format.