Investigating the two-moment characterisation of subcellular biochemical networks - Quantitative Biology > Subcellular ProcessesReport as inadecuate




Investigating the two-moment characterisation of subcellular biochemical networks - Quantitative Biology > Subcellular Processes - Download this document for free, or read online. Document in PDF available to download.

Abstract: While ordinary differential equations ODEs form the conceptual frameworkfor modelling many cellular processes, specific situations demand stochasticmodels to capture the influence of noise. The most common formulation ofstochastic models for biochemical networks is the chemical master equationCME. While stochastic simulations are a practical way to realise the CME,analytical approximations offer more insight into the influence of noise.Towards that end, the two-moment approximation 2MA is a promising addition tothe established analytical approaches including the chemical Langevin equationCLE and the related linear noise approximation LNA. The 2MA approachdirectly tracks the mean and covariance which are coupled in general. Thiscoupling is not obvious in CME and CLE and ignored by LNA and conventional ODEmodels. We extend previous derivations of 2MA by allowing a non-elementaryreactions and b relative concentrations. Often, several elementary reactionsare approximated by a single step. Furthermore, practical situations oftenrequire the use relative concentrations. We investigate the applicability ofthe 2MA approach to the well established fission yeast cell cycle model. Ouranalytical model reproduces the clustering of cycle times observed inexperiments. This is explained through multiple resettings of MPF, caused bythe coupling between mean and covariance, near the G2-M transition.



Author: Mukhtar Ullah, Olaf Wolkenhauer

Source: https://arxiv.org/







Related documents