2014/03/13 by Marianne Rooman, Rooman, Marianne, Jaroslav Albert +3
Biochemistry, Genetics and Molecular Biology · Chemistry · Mathematics · Physics and Astronomy · #Advanced Thermodynamics and Statistical Mechanics #Biomolecules (q-bio.BM) #Cell Behavior (q-bio.CB) #Evolution and Genetic Dynamics #FOS: Biological sciences #Gene Regulatory Network Analysis #Molecular Networks (q-bio.MN) #Stochastic processes and statistical mechanics #thermodynamics and calorimetric analyses
paper · pdf · doi:10.48550/arxiv.1403.3310
openalex publication_date 2014/03/13 · openalex created_date 2022/10/07 · openalex updated_date 2026/07/28
Cell systems consist of a huge number of various molecules that display\nspecific patterns of interactions, which have a determining influence on the\ncell's functioning. In general, such complexity is seen to increase with the\ncomplexity of the organism, with a concomitant increase of the accuracy and\nspecificity of the cellular processes. The question thus arises how the\ncomplexification of systems - modeled here by simple interacting birth-death\ntype processes - can lead to a reduction of the noise - described by the\nvariance of the number of molecules. To gain understanding of this issue, we\ninvestigated the difference between a single system containing molecules that\nare produced and degraded, and the same system - with the same average number\nof molecules - connected to a buffer. We modeled these systems using Ito\nstochastic differential equations in discrete time, as they allow\nstraightforward analytical developments. In general, when the molecules in the\nsystem and the buffer are positively correlated, the variance on the number of\nmolecules in the system is found to decrease compared to the equivalent system\nwithout a buffer. Only buffers that are too noisy by themselves tend to\nincrease the noise in the main system. We tested this result on two model\ncases, in which the system and the buffer contain proteins in their active and\ninactive state, or protein monomers and homodimers. We found that in the second\ntest case, where the interconversion terms are non-linear in the number of\nmolecules, the noise reduction is much more pronounced; it reaches up to 20%\nreduction of the Fano factor with the parameter values tested in numerical\nsimulations on an unperturbed birth-death model. We extended our analysis to\ntwo arbitrary interconnected systems.\n