title: Symmetry in biology: from genetic code to stochastic gene regulation.
abstract: Mathematical models, as instruments for understanding the workings of nature, are a traditional tool of physics, but they also play an ever increasing role in biology--in the description of fundamental processes as well as that of complex systems. In this review, the authors discuss two examples of the application of group theoretical methods, which constitute the mathematical discipline for a quantitative description of the idea of symmetry, to genetics. The first one appears, in the form of a pseudo-orthogonal (Lorentz like) symmetry, in the stochastic modelling of what may be regarded as the simplest possible example of a genetic network and, hopefully, a building block for more complicated ones: a single self-interacting or externally regulated gene with only two possible states: 'on' and 'off'. The second is the algebraic approach to the evolution of the genetic code, according to which the current code results from a dynamical symmetry breaking process, starting out from an initial state of complete symmetry and ending in the presently observed final state of low symmetry. In both cases, symmetry plays a decisive role: in the first, it is a characteristic feature of the dynamics of the gene switch and its decay to equilibrium, whereas in the second, it provides the guidelines for the evolution of the coding rules.
authors.affiliation: Universidade de São Paulo, Instituto de Física de São Carlos, São Carlos, Brazil. aramos@ifsc.usp.br
authors.forename: A F
authors.initials: AF
authors.lastname: Ramos
authors.forename: G C P
authors.initials: GC
authors.lastname: Innocentini
authors.forename: F M
authors.initials: FM
authors.lastname: Forger
authors.forename: J E M
authors.initials: JE
authors.lastname: Hornos
mesh_terms: D000818:Animals; D044127:Epigenesis, Genetic / Q000235:genetics*; D005786:Gene Expression Regulation / Q000502:physiology*; D006801:Humans; D008957:Models, Genetic; D013269:Stochastic Processes; D049490:Systems Biology / Q000379:methods*