A photosynthetic process modelled by a metabolic P system

Photosynthesis is the process used by plants, algae and some bacteria to obtain biochemical energy from sunlight. It is the most important process allowing life on earth. In this work, by applying the Log Gain theory of Metabolic P Systems, we define a mathematical model of an important photosynthetic phenomenon, called Non Photochemical Quenching (shortly NPQ), that determines the plant accommodation to the environmental light. Starting from experimental data of this phenomenon, we are able to deduce a Metabolic P system which provides, in a specific simplified case, the regulation mechanism underling the NPQ process. The dynamics of our model, generated by suitable computational tools, reproduce, with a very good approximation, the observed behaviour of the natural system

Data analysis pipeline from laboratory to MP models

A work\ufb02ow for data analysis is introduced to synthesize \ufb02ux regulation maps of a metabolic system from time series of data observed in laboratory. The procedure is successfully tested on a signi\ufb01cant 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 \ufb01nd out the regulation maps, and interesting experimental results came out in the context of their residual analysis and model validation