Survival of the sparsest: robust gene networks are parsimonious

By Robert D. Leclerc. 2008

251 citations recorded by the source corpus.

Biological gene networks appear to be dynamically robust to mutation, stochasticity, and changes in the environment and also appear to be sparsely connected. Studies with computational models, however, have suggested that denser gene networks evolve to be more dynamically robust than sparser networks. We resolve this discrepancy by showing that misassumptions about how to measure robustness in artificial networks have inadvertently discounted the costs of network complexity. We show that when the costs of complexity are taken into account, that robustness implies a parsimonious network structure that is sparsely connected and not unnecessarily complex; and that selection will favor sparse networks when network topology is free to evolve. Because a robust system of heredity is necessary for the adaptive evolution of complex phenotypes, the maintenance of frugal network complexity is likely a crucial design constraint that underlies biological organization.

Subfields: Genetics, Molecular Biology

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Citations in the corpus

SINCERA: A Pipeline for Single-Cell RNA-Seq Profiling Analysis (2015, background): “Since biological TRNs are known to be sparse [59], it is assumed that the low-order conditional independencies fit well with the full conditional independence structure between variables and can be accurately estimated with only a small number of observations [60].”
Using graph theory to analyze biological networks (2011, background): “Theoretical results show that the selection for robust gene networks will form minimal complexes even more sparsely connected [64], thus a fundamental design constraint could shape the evolution of gene network complexity.”