Canalization and control in automata networks: body segmentation in Drosophila Melanogaster

Manuel Marques-Pita1,2 and Luis M. Rocha1,2

1 School of Informatics and Computing, Indiana University, 919 East Tenth Street, Bloomington IN 47408, USA
2FLAD Computational Biology Collaboratorium, Instituto Gulbenkian de Ciencia, Portugal

Citation: M. Marques-Pita and L.M. Rocha [2013]. "Canalization and control in automata networks: body segmentation in Drosophila Melanogaster". PLoS ONE, 8(3): e55946. doi:10.1371/journal.pone.0055946.

The full text and pdf re-print are available from the PLoS ONE site. Due to mathematical notation and graphics, only the abstract is presented here. The arxiv pre-print is also available. Supplementary materials for this paper are also available.


We present schema redescription as a methodology to characterize canalization in automata networks used to model biochemical regulation and signalling. In our formulation, canalization becomes synonymous with redundancy present in the logic of automata. This results in straightforward measures to quantify canalization in an automaton (micro-level), which is in turn integrated into a highly scalable way to characterize the collective dynamics of large-scale automata networks (macro-level). This way, our approach provides a method to link micro- to macro-level dynamics---a crux of complexity. Several new results ensue from this methodology: uncovering of dynamical modularity (modules in the dynamics rather than in the structure of networks), identification of minimal conditions and critical nodes to control the convergence to attractors, simulation of dynamical behaviour from incomplete information about initial conditions, and measures of macro-level canalization and robustness to perturbations. We exemplify our methodology with a well-known model of the intra- and inter cellular genetic regulation of body segmentation in Drosophila Melanogaster. We use this model to show that our analysis does not contradict any previous findings. But we also obtain new knowledge about its behaviour: a better understanding of the size of its wild-type attractor basin (larger than previously thought), the identification of novel minimal conditions and critical nodes that control wild-type behaviour, and the resilience of these to stochastic interventions. Our methodology is applicable to any complex network that can be modelled using automata, but we focus on biochemical regulation and signalling, towards a better understanding of the (decentralized) control that orchestrates cellular activity---with the ultimate goal of explaining how do cells and tissues "compute".

Keywords:Boolean Networks, Automata Networks, Complex Networks, Complex Systems, Canalization, Canalizing functions, Robustness, Control, Modularity, Dynamics, Self-Organization, Emergent Computation, Gene regulation, Biochemical regulation.

For more information contact Luis Rocha at Check the Web Design Credits, for due credit.
Last Modified: March 9, 2013