F1000Research · 2019 · 16 citations · 15 references
Life SciencesCell BiologyMolecular BiologyCell SignalingComputational BiologyGene Regulatory NetworksBoolean Network ModelsCell Signaling NetworksCellular AutomataEpithelial MorphogenesisEpithelial TissueSignaling NetworksBoolean Gene NetworksBoolean Gene Regulatory NetworksCellular Automaton ModelingEpithelial Tissue DynamicsLogical Framework ApproachQualitative ModelsRegulatory Gene NetworksSignals
Cellular responses are governed by regulatory networks subject to external signals from surrounding cells and to other micro-environmental cues. The logical (Boolean or multi-valued) framework proved well suited to study such processes at the cellular level, by specifying qualitative models of involved signalling pathways and gene regulatory networks. Here, we describe and illustrate the main features of EpiLog, a computational tool that implements an extension of the logical framework to the tissue level. EpiLog defines a collection of hexagonal cells over a 2D grid, which embodies a mono-layer epithelium. Basically, it defines a cellular automaton in which cell behaviours are driven by associated logical models subject to external signals. EpiLog is freely available on the web at http://epilog-tool.org. It is implemented in Java (version ≥1.7 required) and the source code is provided at https://github.com/epilog-tool/epilog under a GNU General Public License v3.0.
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Dynamical analysis of a generic Boolean model for the control of the mammalian cell cycle
Adrien Fauré, Aurélien Naldi, Claudine Chaouiya et al. · Bioinformatics · 2006 · 663 citations · Full text
Life Sciences, Biology, Cell Biology +16