Transport of substances and communication between compartments are fundamental biological processes, often mediated by the presence of complementary proteins attached to the surfaces of membranes. Within compartments, substances are acted upon by local biochemical rules. Inspired by this behaviour we present a model based on membrane systems, with objects attached to the sides of the membranes and floating objects that can move between the regions of the system. Moreover, in each region there are evolution rules that rewrite the transported objects, mimicking chemical reactions. We first analyse the system, showing that interesting qualitative properties can be decided (like reachability of configurations) and then present a simulator based on a stochastic version of the introduced model and show how it can be used to simulate relevant quantitative biological processes. © 2007 Elsevier B.V. All rights reserved.
Membrane Systems with Peripheral Proteins: Transport and Evolution / Cavaliere, M.; Sedwards, S.. - In: ELECTRONIC NOTES IN THEORETICAL COMPUTER SCIENCE. - ISSN 1571-0661. - 171:2(2007), pp. 37-53. ( First Workshop on Membrane Computing and Biologically Inspired Process Calculi (MeCBIC 2006) Italy 2006) [10.1016/j.entcs.2007.05.006].
Membrane Systems with Peripheral Proteins: Transport and Evolution
Cavaliere M.;
2007
Abstract
Transport of substances and communication between compartments are fundamental biological processes, often mediated by the presence of complementary proteins attached to the surfaces of membranes. Within compartments, substances are acted upon by local biochemical rules. Inspired by this behaviour we present a model based on membrane systems, with objects attached to the sides of the membranes and floating objects that can move between the regions of the system. Moreover, in each region there are evolution rules that rewrite the transported objects, mimicking chemical reactions. We first analyse the system, showing that interesting qualitative properties can be decided (like reachability of configurations) and then present a simulator based on a stochastic version of the introduced model and show how it can be used to simulate relevant quantitative biological processes. © 2007 Elsevier B.V. All rights reserved.| File | Dimensione | Formato | |
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