Novel approximation methods for stochastic biochemical kinetics

Statistical Physics and Complexity Group meeting

Novel approximation methods for stochastic biochemical kinetics

  • Event time: 11:30am
  • Event date: 20th March 2013
  • Speaker: Ramon Grima (Systems Biology)
  • Location: Room 2511,

Event details

It is well known that for any chemical system composed of at most first-order reactions, one can obtain the full stochastic properties of the system via an exact solution of the moment equations for the chemical master equation. In contrast for systems composed of bimolecular reactions such an exact solution is not generally possible. Given that most biochemical systems involve such interactions, there is the need of systematic approximation methods to probe the intrinsic noise statistics of realistic biochemical networks. In this talk I will present the Effective Mesoscopic Rate Equation (EMRE) formalism which provides accurate approximations to the mean concentrations predicted by the chemical master equation for systems with molecule numbers as small as the order of ten molecules. These equations correct the conventional rate equations and predict a wide variety of phenomena including amplification of substrate concentrations in metabolic networks and concentration inversions in trimerization and genetic networks. I will also discuss an extension of these ideas to predict noise-induced oscillations in circadian oscillators and a comparison of the EMRE based approaches with conventional moment-closure methods. Finally I'll showcase iNA (intrinsic noise analyzer), our new open-source software with a user- friendly graphical interface, which uses the aforementioned approximation methods to calculate the intrinsic noise statistics of a biochemical network specified by an SBML file.