A workflow for data analysis is introduced to synthesize flux regulation maps of a metabolic system from time series of data observed in laboratory. The procedure is successfully tested on a significant case study, the photosynthetic phenomenon called NPQ, which determines plant accommodation to environmental light. A previously introduced MP model of such a photosynthetic process has been improved, by providing an MP system with a simpler regulative network that reproduces the observed behaviors of the natural system. Two regression techniques were employed to find out the regulation maps, and interesting experimental results came out in the context of their residual analysis and model validation.

Data analysis pipeline from laboratory to MP models

CASTELLINI, ALBERTO;FRANCO, Giuditta;
2011

Abstract

A workflow for data analysis is introduced to synthesize flux regulation maps of a metabolic system from time series of data observed in laboratory. The procedure is successfully tested on a significant case study, the photosynthetic phenomenon called NPQ, which determines plant accommodation to environmental light. A previously introduced MP model of such a photosynthetic process has been improved, by providing an MP system with a simpler regulative network that reproduces the observed behaviors of the natural system. Two regression techniques were employed to find out the regulation maps, and interesting experimental results came out in the context of their residual analysis and model validation.
MP systems; Non-photochemical quenching; NPQ; data analysis; stepwise regression; neural networks; optimization; variable selection; mitotic cycle; MP log-gain; model validation.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11562/341535
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