title: Counting statistics for genetic switches based on effective interaction approximation.
abstract: Applicability of counting statistics for a system with an infinite number of states is investigated. The counting statistics has been studied a lot for a system with a finite number of states. While it is possible to use the scheme in order to count specific transitions in a system with an infinite number of states in principle, we have non-closed equations in general. A simple genetic switch can be described by a master equation with an infinite number of states, and we use the counting statistics in order to count the number of transitions from inactive to active states in the gene. To avoid having the non-closed equations, an effective interaction approximation is employed. As a result, it is shown that the switching problem can be treated as a simple two-state model approximately, which immediately indicates that the switching obeys non-Poisson statistics.
authors.affiliation: Graduate School of Informatics, Kyoto University, Yoshida Hon-machi, Sakyo-ku, Kyoto-shi, Kyoto 606-8501, Japan. ohkubo@i.kyoto-u.ac.jp
authors.forename: Jun
authors.initials: J
authors.lastname: Ohkubo
mesh_terms: D008957:Models, Genetic; D015233:Models, Statistical; D009010:Monte Carlo Method; D011506:Proteins / Q000235:genetics*; D012333:RNA, Messenger / Q000235:genetics*
chemical_list: D011506:Proteins; D012333:RNA, Messenger