Trend-based analysis of a population model of the AKAP scaffold protein

Andrei, O. and Calder, M. (2012) Trend-based analysis of a population model of the AKAP scaffold protein. Lecture Notes in Computer Science, 7625, pp. 1-25. (doi: 10.1007/978-3-642-35524-0_1)

70740.pdf - Accepted Version



We formalise a continuous-time Markov chain with multi-dimensional discrete state space model of the AKAP scaffold protein as a crosstalk mediator between two biochemical signalling pathways. The analysis by temporal properties of the AKAP model requires reasoning about whether the counts of individuals of the same type (species) are increasing or decreasing. For this purpose we propose the concept of stochastic trends based on formulating the probabilities of transitions that increase (resp. decrease) the counts of individuals of the same type, and express these probabilities as formulae such that the state space of the model is not altered. We define a number of stochastic trend formulae (e.g. weakly increasing, strictly increasing, weakly decreasing, etc.) and use them to extend the set of state formulae of Continuous Stochastic Logic. We show how stochastic trends can be implemented in a guarded-command style specification language for transition systems. We illustrate the application of stochastic trends with numerous small examples and then we analyse the AKAP model in order to characterise and show causality and pulsating behaviours in this biochemical system.

Item Type:Articles
Additional Information:Transactions on Computational Systems Biology XIV.
Glasgow Author(s) Enlighten ID:Andrei, Dr Oana and Calder, Professor Muffy
Authors: Andrei, O., and Calder, M.
College/School:College of Science and Engineering > School of Computing Science
Journal Name:Lecture Notes in Computer Science
Copyright Holders:Copyright © 2012 Springer
First Published:First published in Lecture Notes in Computer Science 7625
Publisher Policy:Reproduced in accordance with the copyright policy of the publisher

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