2015
DOI: 10.1007/978-3-319-24953-7_16
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ASSA-PBN: An Approximate Steady-State Analyser of Probabilistic Boolean Networks

Abstract: Abstract. We present ASSA-PBN, a tool for approximate steady-state analysis of large probabilistic Boolean networks (PBNs). ASSA-PBN contains a constructor, a simulator, and an analyser which can approximately compute the steadystate probabilities of PBNs. For large PBNs, such approximate analysis is the only viable way to study their long-run behaviours. Experiments show that ASSA-PBN can handle large PBNs with a few thousands of nodes.

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Cited by 22 publications
(25 citation statements)
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“…The BNs we use for the experiments are randomly generated with ASSA-PBN [19], which can generate random BNs complying with specified parameters, e.g., the number of nodes in the BN and the maximal number of variables of the predictor functions.…”
Section: Discussionmentioning
confidence: 99%
“…The BNs we use for the experiments are randomly generated with ASSA-PBN [19], which can generate random BNs complying with specified parameters, e.g., the number of nodes in the BN and the maximal number of variables of the predictor functions.…”
Section: Discussionmentioning
confidence: 99%
“…The PBN modeller can either load a PBN from a specification file or generate a random PBN (e.g., for benchmarking and testing purposes) complying with a given parametrisation [4]. In ASSA-PBN 2.0, a high-level PBN definition format is provided and visualisation of a PBN is supported in the GUI.…”
Section: Tool Architecture and New Featuresmentioning
confidence: 99%
“…The steady-state distributions can be computed either in an exact way or in a statistical way. Two iterative methods, i.e., the Jacobi method and the Gauss-Seidel method are implemented for exact computation; while three statistical methods, i.e., the perfect simulation, the two-state Markov chain approach, and the Skart method are implemented for the approximate computation [4]. Due to their large memory and time costs, the two iterative methods and the perfect simulation method are only suitable for analysing small-size PBNs [4].…”
Section: Tool Architecture and New Featuresmentioning
confidence: 99%
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