title: Biological models: measuring variability with classical and quantum information.
abstract: This essay proposes methods to analyse the variability of biological data. The idea is to express the state of a biological system as a linear combination of base states in a Hilbert space. Coefficients of the linear combination can be interpreted as probabilities and informational entropy is associated to each state allowing the definition of a classical variability measure. Besides, state transition matrices can also be calculated and their norms express the dynamics of the system organization and a quantum variability measure. As the examples show, the classical measure expresses a structural variability and the quantum measure expresses a functional variability.
authors.affiliation: Departamento de Engenharia de Telecomunições e Controle, Escola Politécnica da Universidade de São Paulo, Av. Prof. Luciano Gualberto, Travessa 3, n. 158, 05508-900 São Paulo, Brazil. piqueira@lac.usp.br
authors.forename: J R C
authors.initials: JR
authors.lastname: Piqueira
authors.forename: F A
authors.initials: FA
authors.lastname: Serboncini
authors.forename: L H A
authors.initials: LH
authors.lastname: Monteiro
mesh_terms: D019295:Computational Biology / Q000379:methods*; D019277:Entropy; D007257:Information Theory; D008954:Models, Biological; D011789:Quantum Theory; D013598:Systems Theory