POSSIBILISTIC METABOLIC FLUX ANALYSIS

In a recent paper we introduce a possibilistic framework to perform metabolic flux estimations using a constraint-based model and a set of measurements, which has the following features:
  • Able to handle inconsistencies (sensors errors and model imprecision) to provide reliable estimations
  • Richer estimates (not only point-wise, but histograms and intervals)
  • Cast as linear programming problems, able to handle thousands of variables with efficiency
  • Exploits the available data – even if those are scarce – to grade the possibility of all the flux states
In summary, we introduce a possibilistic framework for the estimation of metabolic fluxes, which is flexible, reliable, usable in scenarios lacking data and computationally efficient.


DETAILS

You can find details about Poss-MFA and several applications in my PhD Thesis, “Interval and possibilistic methods for constraint-based metabolic models”.


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SOFTWARE

You can download a simple example (matlab file) with the paper.
A software package is under development and will be available in the future (hopefully).
I am always glad of helping those using our methods, so feel free to contact me.


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REFERENCES

[1] Llaneras F, Sala A, Picó J (2009). A possibilistic framework for constraint-based metabolic flux analysis, BMC Systems Biology, 3:73 [article]

[2] Tortajada M, Llaneras F, Picó J (2010). Validation of a constraint-based model of Pichia pastoris growth under data scarcity. BMC Systems Biology, 4:115 [article]

[3] Llaneras F (2011). Interval and possibilistic methods for constraint-based metabolic models. PhD Thesis, Universidad Politécnica de Valencia, Spain. [article]