title: Solving dynamical inverse problems by means of Metabolic P systems.
abstract: MP (Metabolic P) systems are a class of P systems introduced for modelling metabolic processes. We refer to the dynamical inverse problem as the problem of identifying (discrete) mathematical models exhibiting an observed dynamics. In this paper, we complete the definition of the algorithm LGSS (Log-gain Stoichiometric Stepwise regression) introduced in Manca and Marchetti (2011) for solving a general class of dynamical inverse problems. To this aim, we develop a reformulation of the classical stepwise regression in the context of MP systems. We conclude with a short review of two applications of LGSS for discovering the internal regulation logic of two phenomena relevant in systems biology.
authors.affiliation: University of Verona, Department of Computer Science, Italy. vincenzo.manca@univr.it
authors.forename: V
authors.initials: V
authors.lastname: Manca
authors.forename: L
authors.initials: L
authors.lastname: Marchetti
mesh_terms: D000465:Algorithms; D045744:Cell Line, Tumor; D005947:Glucose / Q000378:metabolism; D005951:Glucose Tolerance Test; D006801:Humans; D007328:Insulin / Q000378:metabolism; D053858:Metabolic Networks and Pathways; D008954:Models, Biological; D018719:Erb-b2 Receptor Tyrosine Kinases / Q000235:genetics; D012044:Regression Analysis; D012984:Software; D049490:Systems Biology / Q000379:methods*; D059467:Transcriptome / Q000235:genetics
chemical_list: D005947:Glucose; D007328:Insulin; D018719:Erb-b2 Receptor Tyrosine Kinases; C508053:ERBB2 protein, human