#38 · Systems biology

Noise propagation and feedback topology shape stochastic gene expression persistence

The dominant thread across these preprints is how intrinsic noise in gene regulatory circuits is propagated, persisted, and statistically characterized. One item derives large deviation rate functions for post-transcriptional regulation models by mapping them onto promoter-based models via PPA, extending rare-event analysis beyond the promoter layer. A second applies a linear noise approximation to two-node transcription factor feedback motifs, showing that loop closure produces cyclic noise that sets how long fluctuations persist. The third reexamines Kaneko's evolutionary model of noise-driven robustness, reconstructing its simulation protocol and releasing reusable code; it concerns evolutionary outcomes rather than expression dynamics. What is new is the joint treatment of noise propagation, feedback topology, and rare-event statistics, though all three items are preprints.