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Metabolic P systems are a modeling framework for metabolic, regulatory and signaling processes. The key point of MP systems are flux regulation functions, which determine the evolution of a system from a given initial state. This paper presents important improvements to a technique, based on genetic algorithms and multiple linear regression, for inferring regulation functions that reproduce observed behaviors (time series datasets). An accurate analysis of three case studies, namely the mitotic oscillator in early amphibian embryos, the Lodka-Volterra predator-prey model and the chaotic logistic map show that this methodology can provide, from observed data, significant knowledge about the regulation mechanisms underlying biological processes. [ABSTRACT FROM AUTHOR]

Motivated by an interest to understand how information is organized within genomes, and how genes communicate between each other in the transcription process, in this paper we propose a novel network based methodology for genomic sequence analysis, specifically applied to three organisms: Nanoarchaeum equitans, Escherichia coli, and Saccaromyces cerevisiae. A dictionary based approach previously introduced is here continued through a repeat analysis in genic and intergenic regions. Key results of this work have been found in a biological and computational analysis of novel parametrized gene networks, defined by means of motifs of fixed length occurring inside multiple genes. Cliques emerge as groups of genes sharing a long repeat with a clear biological interpretation, while a (complete, paralog) cluster analysis has outlined some unexpected regularity. Repeat sharing gene networks may be applied in contexts of comparative genomics, as an investigation methodology for a comprehension of evolutional and functional properties of genes. [ABSTRACT FROM AUTHOR]

workflow for data analysis is introduced to synthesize flux regulation maps of a Metabolic P 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 for model validation. [ABSTRACT FROM AUTHOR]

In this work we give a formalization of Hybrid Functional Petri Nets, shortly HFPN, an extension of Petri Nets for biopathways modelling, and we compare them with Metabolic P Systems. An introduction to both the formalisms is given, together with highlights about respective similarities and differences. Their equivalence is thus proved by means of a theorem which holds under quite general hypotheses. The case study of the lac operon gene regulatory mechanism in the glycolytic pathway of Escherichia coli is modeled by an MP system which provides the same dynamics of an equivalent HFPN model. [ABSTRACT FROM AUTHOR]