Computational protocol: A Network Model to Describe the Terminal Differentiation of B Cells

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Protocol publication

[…] Boolean networks constitute the simplest approach to modeling the dynamics of regulatory networks. A Boolean network consists of a set of nodes, each of which may attain only one of two states: 0 if the node is OFF, or 1 if the node is ON [, ]. The level of activation for the i-th node is represented by a discrete variable xi, which is updated at discrete time steps according to a Boolean function Fi such that xi(t+1) = Fi[x1(t), x2(t), …, xn(t)], where [x1(t), x2(t), …, xn(t)] is the activation state of the regulators of the node xi at time t. The Boolean function Fi is expressed using the logic operators ∧ (AND), ∨ (OR), and ¬ (NOT). In our model, all Fis are updated simultaneously, which is known as the synchronous approach. The resulting set of Fis is shown in .We obtained all the attractors of the Boolean model by testing all possible initial states under a synchronous updating scheme using the R package BoolNet []. Moreover, we simulated all possible single loss- and gain-of-function mutants by fixing the value of each node to 0 or 1, respectively.The complete discrete model is available for testing in The Cell Collective (http://www.thecellcollective.org/) model B cell differentiation []. Furthermore, the model is available as the accompanying file (Bcells_model.xml) in SBMLqual format. […]

Pipeline specifications

Software tools BoolNet, Cell Collective
Application Mathematical modeling