Probabilistic Flux Balance Analysis (PFBA)

The Probabilistic Flux Balance Analysis (PFBA) is a principled approach for using gene expression profiles to improve predictions of metabolic reaction rates. This new computational framework formulates probabilistic signatures by incorporating gene expression profiles in to the regulatory network linking with genomic-scale metabolic models. With the framework, cellular growth rates influenced by deletion of a regulatory gene or in combination of regulatory genes can be predicted in silico.

PFBA Guide
 
Installation requirements
  • PFBA is a Python-package and therefore the installation of Python is required
    Install Ubuntu 14.04
    Install gurobi, including the Python extension
    Download python-bpfba and run './prepare-ubuntu1404.sh'
    Done, now you can run the python-bpfba scripts.
    Run python-bpfba. Run: 'cd ~/ python run-tb.py', 'python run-fendt.py', etc.
    Download Constanzo's data to run double knockout from: http://drygin.ccbr.utoronto.ca/~costanzo2009/sgadata_costanzo2009_rawdata_101120.txt.gz
    Run: 'cd ~/ python run-double.py'
  • Download

    Latest version

    RAVEN Github page

    Pre trained HMMs:      
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    Older versions: