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  1. Proceedings of the 8th International Conference on Computational Methods in Systems Biology (CMSB '10)
  2. Understanding signalling networks as collections of signal transduction pathways
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From species to pathway and tissue as process
Building cell-like structures from the bottom-up
Discrete causal model view of biological networks
Steady-state solution of biochemical systems, beyond S-systems via T-invariants
On verifying Bio-PEPA models
Target driven biochemical network reconstruction based on petri nets and simulated annealing
A generic abstract machine for stochastic process calculi
Hybrid numerical solution of the chemical master equation
Action-based analysis of discrete regulatory networks with short-term stimuli
Stochasticity in reactions: a probabilistic Boolean modeling approach
Understanding signalling networks as collections of signal transduction pathways
A comparative study of stochastic analysis techniques
Structural identification of GMA models: algorithm and model comparison

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Understanding signalling networks as collections of signal transduction pathways

Content Provider ACM Digital Library
Author Knapp, Merrill Donaldson, Robin Talcott, Carolyn Calder, Muffy
Abstract A signalling network is a network of reactions that govern how a cell responds to its environment. A pathway is a dynamic flow of "signal" through the network (signal transduction), for example from a receptor to a transcription factor that enables expression of a gene. In this paper we introduce a method to compute all pathways in a signalling network that satisfy a simple property constraining initial, final and intermediate states. This method, concerned with signal transduction, is compared to the steady state view underlying Petri net place/transition invariants and flux balance analysis. We apply the method to the signalling network model being developed in the Pathway Logic project and identify knockout/inhibition targets and common (pathway) events. This approach also allows us to better understand and formalise the interaction between pathways in a network, for example to identifying pathway inhibition targets that limit the effect on unrelated pathways.
Starting Page 86
Ending Page 95
Page Count 10
File Format PDF
ISBN 9781450300681
DOI 10.1145/1839764.1839775
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2010-09-29
Publisher Place New York
Access Restriction Subscribed
Subject Keyword T invariants Pathways Reaction minimal paths Signalling networks
Content Type Text
Resource Type Article
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