Dynamical and Structural Modularity of Discrete Regulatory Networks
Please always quote using this URN:urn:nbn:de:0296-matheon-6242
- A biological regulatory network can be modeled as a discrete function f that contains all available information on network component interactions. From f we can derive a graph representation of the network structure as well as of the dynamics of the system. In this paper we introduce a method to identify modules of the network that allow us to construct the behavior of f from the dynamics of the modules. Here, it proves useful to distinguish between dynamical and structural modules, and to define network modules combining aspects of both. As a key concept we establish the notion of symbolic steady state, which basically represents a set of states where the behavior of f is in some sense predictable, and which gives rise to suitable network modules. We apply the method to a regulatory network involved in T helper cell differentiation.
Author: | Heike Siebert |
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URN: | urn:nbn:de:0296-matheon-6242 |
Referee: | Alexander Bockmayr |
Document Type: | Preprint, Research Center Matheon |
Language: | English |
Date of first Publication: | 2009/07/21 |
Release Date: | 2009/07/21 |
Institute: | Freie Universität Berlin |
Preprint Number: | 627 |