Canalization reduces the nonlinearity of regulation in biological networks
arxiv(2024)
摘要
Biological networks such as gene regulatory networks possess desirable
properties. They are more robust and controllable than random networks. This
motivates the search for structural and dynamical features that evolution has
incorporated in biological networks. A recent meta-analysis of published,
expert-curated Boolean biological network models has revealed several such
features, often referred to as design principles. Among others, the biological
networks are enriched for certain recurring network motifs, the dynamic update
rules are more redundant, more biased and more canalizing than expected, and
the dynamics of biological networks are better approximable by linear and
lower-order approximations than those of comparable random networks. Since most
of these features are interrelated, it is paramount to disentangle cause and
effect, that is, to understand which features evolution actively selects for,
and thus truly constitute evolutionary design principles. Here, we show that
approximability is strongly dependent on the dynamical robustness of a network,
and that increased canalization in biological networks can almost completely
explain their recently postulated high approximability.
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