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Open Access Highly Accessed Methodology article

Stochastic Boolean networks: An efficient approach to modeling gene regulatory networks

Jinghang Liang and Jie Han*

Author Affiliations

Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB T6G 2V4, Canada

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BMC Systems Biology 2012, 6:113  doi:10.1186/1752-0509-6-113

Published: 28 August 2012

Additional files

Additional file 1:

Stochastic Logic using Non-Bernoulli Sequences.

Format: PDF Size: 141KB Download file

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Additional file 2:

mux2.m. ‘mux2.m’ is a Matlab program, which implements the function of a two-input stochastic multiplexer (MUX, with one control input) for an SBN.

Format: M Size: 1KB Download file

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Additional file 3:

mux4.m. ‘mux4.m’ is a Matlab program, which implements the function of a four-input stochastic multiplexer (MUX, with two control inputs) for an SBN.

Format: M Size: 1KB Download file

Open Data

Additional file 4:

Truth Table of the PBN Inferred from the T Cell Microarray Time Series Data.

Format: PDF Size: 75KB Download file

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Additional file 5:

T_cell_SBN.m. ‘T_cell_SBN.m’ is a Matlab program, which describes the structure of an SBN for the T-cell genetic network and computes its state transition matrix for both without and with perturbation. The programs ‘mux2.m’ and ‘mux4.m’ are needed to run ‘T_cell_SBN.m.’

Format: M Size: 5KB Download file

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Additional file 6:

time_frame_expansion.m. ‘time_frame_expansion.m’ is a Matlab program, which evaluates the steady state distribution using the time frame expansion technique for the T-cell genetic network. The programs ‘mux2.m’ and ‘mux4.m’ are needed to run ‘time_frame_expansion.m.’

Format: M Size: 5KB Download file

Open Data