Living organisms are complex, dynamical and dissipative systems, often considered to be in a far from equilibrium state. That is, for their survival, living systems exchange matter dynamically and are able to evolve spontaneously under certain environmental perturbation towards a critical point for a phase transition. This happens without fine-tuning their system parameters. The formation of biofilm by certain microorganisms, such as Escherichia coliand Saccharomyces cerevisiae, is a common example. Such phase transformation is known to break the symmetry of the system leaving it invariant, or in a collective mode. At the critical point, the system achieves universality, that is, all differences between individuals will be reduced to follow common “universal” properties. The fascinating self-organizing behavior of biology has triggered scientists across diverse disciplines to study the underlying syncmechanisms. Non-linear Kuramoto model has been used to study synchronized or syncbehavior in numerous fields, however, its application in biology is scare. Here, I introduce the non-linear model and show that large scale “small-world” or “scale-free” networks are crucial for spontaneous synceven for low coupling strength. To verify this prediction, we performed multi-dimensional transcriptome-wide analysis of Saccharomyces cerevisiaebiofilm in wildtype and 6 biofilm regulating overexpression strains (DIG1, SAN1, TOS8, ROF1, SFL1, HEK2). The overall results show that low to middle expressed genes, not the highly expressed, are key for scale invariance in biology. Together, our data indicate that scale-free network connectivity structure with low coupling, or expression levels, is sufficient for sync behavior of living cells.