Boolean Networks

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First proposed by Stuart Kauffman[1], Boolean Network (BN) is a way to model the dynamics of Gene Regulatory Networks. A Boolean Network is comprised of gene states and their corresponding input (update) functions. Each gene takes on the value of either 1 or 0 (ON or OFF), and the state of the gene is the realization of inputs from the previous time step. In a general case of Random Boolean Networks,

Following the convention of BN/PBN Toolbox (Lähdesmäki & Shmulevich)[2], we have developed a general framework for implementing Multicell Boolean Networks[3] in Biocellion. In Multicell Boolean Networks, the user is able to implement up to two different Boolean Networks for specified cells. It requires users to input 5 parameter files: Cell Location File (i.e. pcc_qwang_phi0.12.txt), NV File (i.e. pcc_qwang_.nv), Truth Table File (i.e. pcc_qwang.tt), varF File (i.e. pcc_qwang.varf), Initial State File (i.e. pcc_qwang_phi0.12.st).

Cell Location File

Users initialize cell information in Cell Location File. In the first line, users set the number of cells to be used for BNs. Starting in the second line, users set the cell location on the simulation domain, size of the cells, and an additional free parameter.

NV File

Users set the number of input variables for each gene. The length of each row is the number of genes in a cell, and the max number of inputs cannot exceed max connectivity of a network. If you're modeling two different BN types, there should be a second row of number of input variables on the next line.

Truth Table File

Users set the update function rule via the Truth Table File. If a gene doesn't contribute in updating of a state, leave it as '-1'.

varF File

Users set how the genes are wired. The number of non-negative-one entries in each column must be equal to the row specified in the NV file.

Initial State File

Users set the initial states of all the cells. The number of rows must be equal to the number of cells specified in Cell Location File, and the number of columns must equal the number of genes.

-Work In Progress
  1. Kauffman, S. A. (1969). "Metabolic stability and epigenesis in randomly constructed genetic nets". Journal of Theoretical Biology. 22 (3): 437–467. doi:10.1016/0022-5193(69)90015-0. PMID 5803332
  2. http://www.mybiosoftware.com/bnpbn-toolbox-toolbox-boolean-networks-probabilistic-boolean-networks.html
  3. https://github.com/boaguilar/multicell_boolean_networks