Analysis of Discrete Bioregulatory Networks Using Symbolic Steady States
Please always quote using this URN:urn:nbn:de:0296-matheon-5622
- A discrete model of a biological regulatory network can be represented as a discrete function f that contains all available information on interactions between network components and the rules governing the evolution of the network in the discrete state space. Both the information on the structure as well as the dynamics of the system can be represented as directed graphs. Since the state space size grows exponentially with the number of network components, analysis of large networks is a complex problem. In this paper, we introduce the notion of symbolic steady state that allows us to identify subnetworks that govern the dynamics of the original network in at least a subset of state space. We then state rules to explicitly construct attractors of the system from subnetwork attractors. A further application of the underlying concept allows us to formulate sufficient conditions for the existence of multiple attractors resp. a cyclic attractor based on the existence of positive resp. negative feedback circuits in the structure graph. All results are discussed for dynamics derived from f via the synchronous as well as the asynchronous update rule.
Author: | Heike Siebert |
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URN: | urn:nbn:de:0296-matheon-5622 |
Referee: | Alexander Bockmayr |
Document Type: | Preprint, Research Center Matheon |
Language: | English |
Date of first Publication: | 2009/02/18 |
Release Date: | 2009/02/16 |
Institute: | Freie Universität Berlin |
Preprint Number: | 555 |