Mapping of statistical physics to information theory with application to biological systems.
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.
Rojdestvenski
I
I
Department of Plant Physiology, Umea University, Umea, 90187, Sweden. igor.rojdestvenski@plantphy.umu.su
Cottam
M G
MG
D000818:Animals; D055592:Biophysical Phenomena; D001703:Biophysics; D019295:Computational Biology; D007257:Information Theory; D008660:Metabolism; D013223:Statistics as Topic