An original solution for a all-in-one workspace.
Use either a pre-set pipeline or customize your own metabolic network reconstruction workflow with integrated or other tools.
Five main modules: the PADMet core, the input manager, the user workspace based on Docker technology, the format for storing data and metadata and the included tools.
A whole pool of metadata is associated to the model or its reconstruction and managed by the AuReMe workspace for storage and wiki-visualization.
Interest of heterogeneous methods in pathway completion and filling, thanks to tracking of process metadata.
A tracking system enables to reproduce the exact and complete analysis process automatically, by a simple command sequence.
The DYLISS team has developped an imaginative solution to make genome-scale metabolic network reconstructions to enhance Research...
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A all-in-one Docker image
Package available on Pypi
Tools available on Gitlab
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