title: Fluctuation-preserving coarse graining for biochemical systems.
abstract: Finite stochastic Markov models play a major role in modeling biological systems. Such models are a coarse-grained description of the underlying microscopic dynamics and can be considered mesoscopic. The level of coarse-graining is to a certain extent arbitrary since it depends on the resolution of accommodating measurements. Here we present a systematic way to simplify such stochastic descriptions which preserves both the meso-micro and the meso-macro connections. The former is achieved by demanding locality, the latter by considering cycles on the network of states. Our method preserves fluctuations of observables much better than naïve approaches.
authors.affiliation: Max-Planck-Institut für Dynamik und Selbstorganisation, 37077 Göttingen, Germany.
authors.forename: Bernhard
authors.initials: B
authors.lastname: Altaner
authors.forename: Jürgen
authors.initials: J
authors.lastname: Vollmer
mesh_terms: D000244:Adenosine Diphosphate / Q000737:chemistry; D000255:Adenosine Triphosphate / Q000737:chemistry / Q000378:metabolism; D016547:Kinesins / Q000737:chemistry / Q000378:metabolism; D007700:Kinetics; D008390:Markov Chains; D008954:Models, Biological; D008956:Models, Chemical; D010710:Phosphates / Q000737:chemistry / Q000378:metabolism; D013816:Thermodynamics
chemical_list: D010710:Phosphates; D000244:Adenosine Diphosphate; D000255:Adenosine Triphosphate; D016547:Kinesins