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Parameter Identification and Assessment of Nutrient Transporters in AM Symbiosis through Stochastic Simulations

Authors: SCIACCA, EVA; SPINELLA, SALVATORE; CALCAGNO, CRISTINA; DAMIANI, Ferruccio; COPPO, Mario;

Parameter Identification and Assessment of Nutrient Transporters in AM Symbiosis through Stochastic Simulations

Abstract

AbstractThis paper presents a methodology for identifying the kinetic parameters of a biological system and their relationships with the concentration variations of the species by means of in silico experiments. A nonlinear goal programming technique is employed to identify the kinetic parameters that best satisfy the biological hypothesis of the system behaviour. The simulations are performed on a stochastic simulator for the Calculus of Wrapped Compartments. The extraction of parameters with optimization techniques is usually applied to systems modeled by means of differential equations. Its application in a stochastic framework is rather new. The methodology may open a new path for the investigation of a broader class of biochemical systems (including those that cannot be easily modeled by differential equations) when in vitro experimental measurements are unavailable. The methodology is applied to model the nutrient exchanges in arbuscular mycorrhiza, the most wide-spread plant/fungus symbiosis focusing in particular to a newly discovered ammonium transporter: LjAMT2;2. This case study of ammonia and phosphate plant uptake from the fungus has been dissected in known and hypothetical mechanisms. The results of the analysis provide setting of recent experimental results of carrier LjAMT2;2 and support new insights into biological hypotheses to be put in place.

Keywords

Optimization, CWC, General Computer Science, Systems Biology, Formal Calculi, Systems Biology; Formal Calculi; CWC; Mycorrhizal Symbiosis; Optimization; Parameter Identification, Mycorrhizal Symbiosis, Parameter Identification, Theoretical Computer Science, Computer Science(all)

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This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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