Correlated fluctuations carry signatures of gene regulatory network dynamics.
The dynamics of transcriptional control involve small numbers of molecules and result in significant fluctuations in protein and mRNA concentrations. The correlations between these intrinsic fluctuations then offer, via the fluctuation dissipation relation, the possibility of capturing the system's response to external perturbations, and hence the nature of the regulatory activity itself. We show that for simple regulatory networks of activators and repressors, the correlated fluctuations between molecular species show distinct characteristics for changes in regulatory mechanism and for changes to the topology of causal influence. Here, we do a stochastic analysis and derive time-dependent correlation functions between molecular species of regulatory networks and present analytical and numerical results on peaks and delays in correlations between proteins within networks. Upon using these values of peaks and delays as a two-dimensional feature space, we find that different regulatory mechanisms separate into distinct clusters. This indicates that experimentally observable pairwise correlations can distinguish between gene regulatory networks.
Pakka
Vijayanarasimha H
VH
School of Electronics and Computer Science, University of Southampton, Southampton SO171BJ, UK.
Prügel-Bennett
Adam
A
Dasmahapatra
Srinandan
S
D000465:Algorithms; D016000:Cluster Analysis; D020869:Gene Expression Profiling; D005786:Gene Expression Regulation / Q000235:genetics*; D053263:Gene Regulatory Networks / Q000235:genetics*; D008957:Models, Genetic; D011506:Proteins / Q000235:genetics / Q000378:metabolism; D012333:RNA, Messenger / Q000235:genetics / Q000378:metabolism
D011506:Proteins; D012333:RNA, Messenger