Single molecule dynamics and statistical fluctuations of gene regulatory networks: a repressilator.
The authors developed a time dependent method to study the single molecule dynamics of a simple gene regulatory network: a repressilator with three genes mutually repressing each other. They quantitatively characterize the time evolution dynamics of the repressilator. Furthermore, they study purely dynamical issues such as statistical fluctuations and noise evolution. They illustrated some important features of the biological network such as monostability, spirals, and limit cycle oscillation. Explicit time dependent Fano factors which describe noise evolution and show statistical fluctuations out of equilibrium can be significant and far from the Poisson distribution. They explore the phase space and the interrelationships among fluctuations, order, amplitude, and period of oscillations of the repressilators. The authors found that repressilators follow ordered limit cycle orbits and are more likely to appear in the lower fluctuating regions. The amplitude of the repressilators increases as the suppressing of the genes decreases and production of proteins increases. The oscillation period of the repressilators decreases as the suppressing of the genes decreases and production of proteins increases.
Kim
Keun-Young
KY
Department of Physics and Astronomy, State University of New York at Stony Brook, Stony Brook, New York 11790, USA.
Lepzelter
David
D
Wang
Jin
J
D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D004247:DNA / Q000378:metabolism; D020869:Gene Expression Profiling / Q000379:methods*; D008954:Models, Biological; D008957:Models, Genetic; D015233:Models, Statistical; D008962:Models, Theoretical; D016012:Poisson Distribution; D012333:RNA, Messenger / Q000378:metabolism; D013269:Stochastic Processes; D013997:Time Factors
D012333:RNA, Messenger; D004247:DNA