title: Mapping of statistical physics to information theory with application to biological systems.
abstract: The problem of achieving a mapping of formalisms in statistical physics and theoretical biology to information theory is discussed using an example for canonical ensembles. We extend the meaning of the Handscomb Monte-Carlo method to a general recipe for the transformation from a "configuration" space to a "sentence" space. The ensemble of "sentences" and its corresponding source uncertainty function are introduced. A possible mapping procedure based on a generalization of the Handscomb representation is described. For a biological illustration, we present a way to introduce a pathway representation to describe metabolic processes in living systems.
authors.affiliation: Department of Plant Physiology, Umea University, Umea, 90187, Sweden. igor.rojdestvenski@plantphy.umu.su
authors.forename: I
authors.initials: I
authors.lastname: Rojdestvenski
authors.forename: M G
authors.initials: MG
authors.lastname: Cottam
mesh_terms: D000818:Animals; D055592:Biophysical Phenomena; D001703:Biophysics; D019295:Computational Biology; D007257:Information Theory; D008660:Metabolism; D013223:Statistics as Topic