2008/02/04 by Matti Nykter, Nathan D. Price, Maximino Aldana +5 · 3 citations
Biochemistry, Genetics and Molecular Biology · #Gene Regulatory Network Analysis #Bioinformatics and Genomic Networks #Protein Structure and Dynamics #Criticality #Systems biology #Computational biology #Biology #Adaptability #Gene expression #Computer science #Dynamical systems theory #Biological system #Statistical physics #Gene #Physics #Genetics #Ecology
paper · doi:10.1073/pnas.0711525105
openalex publication_date 2008/02/04 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01
Cells are dynamical systems of biomolecular interactions that process information from their environment to mount diverse yet specific responses. A key property of many self-organized systems is that of criticality: a state of a system in which, on average, perturbations are neither dampened nor amplified, but are propagated over long temporal or spatial scales. Criticality enables the coordination of complex macroscopic behaviors that strike an optimal balance between stability and adaptability. It has long been hypothesized that biological systems are critical. Here, we address this hypothesis experimentally for system-wide gene expression dynamics in the macrophage. To this end, we have developed a method, based on algorithmic information theory, to assess macrophage criticality, and we have validated the method on networks with known properties. Using global gene expression data from macrophages stimulated with a variety of Toll-like receptor agonists, we found that macrophage dynamics are indeed critical, providing the most compelling evidence to date for this general principle of dynamics in biological systems.