Brief paper: Structural properties of continuous representations of Boolean functions for gene network modelling

Authors:
Saadia Faisal;Gerwald Lichtenberg;Saskia Trump;Sabine Attinger
Affiliations:
Department of Computational Hydrosystems, Helmholtz Center for Environmental Research, 04318 Leipzig, Germany;Institute of Control Systems, Hamburg University of Technology, 21073 Hamburg, Germany;Department of Environmental Immunology, Helmholtz Center for Environmental Research, 04318 Leipzig, Germany;Department of Computational Hydrosystems, Helmholtz Center for Environmental Research, 04318 Leipzig, Germany
Venue:
Automatica (Journal of IFAC)
Year:
2010

Citing 5
Cited 0

Boolean functions with engineering applications and computer programs

Boolean functions with engineering applications and computer programs
A model of transcriptional regulatory networks based on biases in the observed regulation rules

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On Learning Gene Regulatory Networks Under the Boolean Network Model

Machine Learning
Algorithms for finding small attractors in boolean networks

EURASIP Journal on Bioinformatics and Systems Biology
Polynomial models of gene dynamics

Neurocomputing

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Abstract

This paper recaps and extends a new method for the parameter identification of Boolean models with continuous valued data. The proposed Zhegalkin identification method with constraints allows us to include a priori known qualitative properties of the system formulated as binary rules. One rule is especially investigated, i.e. the canalizing property-because of its relevance in gene network modelling from which an application example is given.