title: Computing molecular fluctuations in biochemical reaction systems based on a mechanistic, statistical theory of irreversible processes.
abstract: We discuss the quantification of molecular fluctuations in the biochemical reaction systems within the context of intracellular processes associated with gene expression. We take the molecular reactions pertaining to circadian rhythms to develop models of molecular fluctuations in this chapter. There are a significant number of studies on stochastic fluctuations in intracellular genetic regulatory networks based on single cell-level experiments. In order to understand the fluctuations associated with the gene expression in circadian rhythm networks, it is important to model the interactions of transcriptional factors with the E-boxes in the promoter regions of some of the genes. The pertinent aspects of a near-equilibrium theory that would integrate the thermodynamical and particle dynamic characteristics of intracellular molecular fluctuations would be discussed, and the theory is extended by using the theory of stochastic differential equations. We then model the fluctuations associated with the promoter regions using general mathematical settings. We implemented ubiquitous Gillespie's algorithms, which are used to simulate stochasticity in biochemical networks, for each of the motifs. Both the theory and the Gillespie's algorithms gave the same results in terms of the time evolution of means and variances of molecular numbers. As biochemical reactions occur far away from equilibrium-hence the use of the Gillespie algorithm-these results suggest that the near-equilibrium theory should be a good approximation for some of the biochemical reactions.
authors.affiliation: Department of Molecular Biosciences, Centre for Advanced Computational Solutions (C-fACS), Lincoln University, Lincoln, Christchurch, New Zealand.
authors.forename: Don
authors.initials: D
authors.lastname: Kulasiri
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D024721:E-Box Elements / Q000502:physiology; D005786:Gene Expression Regulation; D008954:Models, Biological; D011485:Protein Binding; D014157:Transcription Factors / Q000502:physiology
chemical_list: D014157:Transcription Factors