title: Information theory based approaches to cellular signaling.
abstract: BACKGROUND
  Cells interact with their environment and they have to react adequately to internal and external changes such changes in nutrient composition, physical properties like temperature or osmolarity and other stresses. More specifically, they must be able to evaluate whether the external change is significant or just in the range of noise. Based on multiple external parameters they have to compute an optimal response. Cellular signaling pathways are considered as the major means of information perception and transmission in cells.
  
  
  METHODS
  Here, we review different attempts to quantify information processing on the level of individual cells. We refer to Shannon entropy, mutual information, and informal measures of signaling pathway cross-talk and specificity.
  
  
  CONCLUSIONS
  Information theory in systems biology has been successfully applied to identification of optimal pathway structures, mutual information and entropy as system response in sensitivity analysis, and quantification of input and output information.
  
  
  CONCLUSIONS
  While the study of information transmission within the framework of information theory in technical systems is an advanced field with high impact in engineering and telecommunication, its application to biological objects and processes is still restricted to specific fields such as neuroscience, structural and molecular biology. However, in systems biology dealing with a holistic understanding of biochemical systems and cellular signaling only recently a number of examples for the application of information theory have emerged. This article is part of a Special Issue entitled Systems Biology of Microorganisms.
authors.affiliation: Humboldt-Universitat zu Berlin, Berlin, Germany. christian.waltermann@hu-berlin.de
authors.forename: Christian
authors.initials: C
authors.lastname: Waltermann
authors.forename: Edda
authors.initials: E
authors.lastname: Klipp
mesh_terms: D000818:Animals; D006801:Humans; D007257:Information Theory; D008962:Models, Theoretical; D015398:Signal Transduction / Q000502:physiology*