Find active modules in metabolic networks using high-throughput data

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IMPORTANT: Since publication of the AMBIENT method in BMC Sys Bio, several updates have been made. If you wish to use the version used in the paper it is v0.6.3, however I recommend using the latest version which works in the same way but with additional options and has stability and performance improvements. Thanks for your interest!

AMBIENT (Active Modules for Bipartite Networks) is a Python module that uses simulated annealing to find areas of a metabolic network (modules) that have some consistent characteristic. AMBIENT does not require predefined pathways and gives highly specific predictions of affected areas of metabolism.

For example, scores for reactions based on transcriptional data of their annotated encoding genes can be used in the network and modules of coordinated expression changes can be found. This provides an alternative to pathway/gene set enrichment analyses which is simultaneously more flexible and more specific.





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