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Stochastic Semantics of Signaling as a Composition of Agent-view Automata

Koeppl, H. and Petrov, T. (2011):
Stochastic Semantics of Signaling as a Composition of Agent-view Automata.
In: Electronic Notes in Theoretical Computer Science, pp. 3-17, 272, [Online-Edition: http://linkinghub.elsevier.com/retrieve/pii/S157106611100069...],
[Article]

Abstract

In this paper we present a formalism based on stochastic automata to describe the stochastic dynamics of signal transduction networks that are specified by rule-sets. Our formalism gives a modular description of the underlying stochastic process, in the sense that it is a composition of smaller units, agent-views. The view of an agent is an automaton that identifies all local modification changes of that agent (internal state modifications, binding and unbinding), but also those of interacting agents, which are tested within the same rule. We show how to represent the generator matrix of the underlying Markov process of the whole rule-set as Kronecker sums of the rate matrices belonging to individual view-automata. In the absence of birth the automata are finite, since the number of different contexts in which one agent can appear in a rule-set is finite. We illustrate the framework by an example that is related to cellular signaling events. © 2011 Elsevier B.V. All rights reserved.

Item Type: Article
Erschienen: 2011
Creators: Koeppl, H. and Petrov, T.
Title: Stochastic Semantics of Signaling as a Composition of Agent-view Automata
Language: English
Abstract:

In this paper we present a formalism based on stochastic automata to describe the stochastic dynamics of signal transduction networks that are specified by rule-sets. Our formalism gives a modular description of the underlying stochastic process, in the sense that it is a composition of smaller units, agent-views. The view of an agent is an automaton that identifies all local modification changes of that agent (internal state modifications, binding and unbinding), but also those of interacting agents, which are tested within the same rule. We show how to represent the generator matrix of the underlying Markov process of the whole rule-set as Kronecker sums of the rate matrices belonging to individual view-automata. In the absence of birth the automata are finite, since the number of different contexts in which one agent can appear in a rule-set is finite. We illustrate the framework by an example that is related to cellular signaling events. © 2011 Elsevier B.V. All rights reserved.

Journal or Publication Title: Electronic Notes in Theoretical Computer Science
Volume: 272
Uncontrolled Keywords: Cell signaling,Continuous-time Markov chain,Stochastic automata composition
Divisions: 18 Department of Electrical Engineering and Information Technology > Institute for Telecommunications > Bioinspired Communication Systems
18 Department of Electrical Engineering and Information Technology
18 Department of Electrical Engineering and Information Technology > Institute for Telecommunications
Date Deposited: 04 Apr 2014 12:27
Official URL: http://linkinghub.elsevier.com/retrieve/pii/S157106611100069...
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