Publication Date: 22 Mar 2011
Type: Original Research
Journal: Gene Regulation and Systems Biology
Citation: Gene Regulation and Systems Biology 2011:5 27-40
doi: 10.4137/GRSB.S6804
In this paper, a new model of self-organized criticality is introduced. This model, called the gene expression paradigm, is motivated by the problem of gene expression initiation in the newly-born daughter cells after mitosis. The model is fundamentally different in dynamics and properties from the well known sand-pile paradigm. Simulation experiments demonstrate that a critical total number of proteins exists below which transcription is impossible. Above this critical threshold, the system enters the regime of self-sustained oscillations with standard deviations and periods proportional to the genes' complexities with probability one. The borderline between these two regimes is very sharp. Importantly, such a self-organization emerges without any deterministic feedback loops or external supervision, and is a result of completely random redistribution of proteins between inactive genes. Given the size of the genome, the domain of self-organized oscillatory motion is also limited by the genes' maximal complexities. Below the critical complexity, all the regimes of self-organized oscillations are self-similar and largely independent of the genes' complexities. Above the level of critical complexity, the whole-genome transcription is impossible. Again, the borderline between the domains of oscillations and quiescence is very sharp. The gene expression paradigm is an example of cellular automata with the domain of application potentially far beyond its biological context. The model seems to be simple enough for staging an experiment for verification of its remarkable properties.
PDF (1.62 MB PDF FORMAT)
RIS citation (ENDNOTE, REFERENCE MANAGER, PROCITE, REFWORKS)
BibTex citation (BIBDESK, LATEX)
PMC HTML
The reviewing and editorial management of our paper was timely, thorough, and systematic. In particular the reviewers' comments resulted in a paper significantly more robust than the first version.
Facebook Google+ Twitter
Pinterest Tumblr YouTube