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Find active modules in metabolic networks using high-throughput data
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.
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sarface is a user-interface to the sysstat/sar database which inputs data from sar and plots to a live X11 graph via gnuplot. It mimics the cmd-line options from sar but can cross-plot any two or more stats and apply simple mathematical functions them.
...Among trimAl’s additional features, trimAl allows getting the complementary alignment (columns that were trimmed), to compute statistics from the alignment, to select the output file format , to get a summary of trimAl’s trimming in HTML and SVG formats, and many other options.
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