Evolving noisy oscillatory dynamics in genetic regulatory networks

We introduce a genetic programming (GP) approach for evolving genetic networks that demonstrate desired dynamics when simulated as a discrete stochastic process. Our representation of genetic networks is based on a biochemical reaction model including key elements such as transcription, translation and post-translational modifications. The stochastic, reaction-based GP system is similar but not identical with algorithmic chemistries. We evolved genetic networks with noisy oscillatory dynamics. The results show the practicality of evolving particular dynamics in gene regulatory networks when modelled with intrinsic noise.

Dynamics of a transient wave group breaking on a beach

New experimental data are presented on the dynamics of a transient wave group breaking on a beach. The transient group is tracked during shoaling and wave breaking, together with the long waves forced during those processes. High spatial sampling enables novel resolution of the evolution of the wave envelope during breaking and the correlation between the envelope and the long waves. The data show a strong dynamic long wave setup in front of the group in shallow water. The amplitude of the dynamic setup is likely to be a function of beach slope, and larger on steeper beaches.