Bioinformatics Vol. 16 no. 6 2000
Pages 527-533
© 2000 Oxford University Press
Original Paper |
Comparing systemic properties of ensembles of biological networks by graphical and statistical methods
1 Department of Microbiology and Immunology,
University of Michigan Medical School, 5641 Medical Science
Building II Ann Arbor, MI 48109-0620, USA
2 Grupo de Bioquimica e Biologia Teoricas,
Instituto Rocha Cabral, Calcada Bento da Rocha Cabral 14, 1250
Lisboa, Portugal
3 Programa Gulbenkian de Doutoramentos em
Biologia e Medicina, Departamento de Ensino, Instituto Gulbenkian
de Ciência, Rua da Quinta Grande 6,
1800 Oeiras, Portugal
Received on July 28, 1999
; revised on November 11, 1999
; accepted on December 3, 1999
Motivation: When dealing with questions that concern a general class of models for biological networks, large numbers of distinct models within the class can be grouped into an ensemble that gives a statistical view of the properties for the general class. Comparing properties of different ensembles through the use of point measures (e.g. medians, standard deviations, correlation coefficients) can mask inhomogeneities in the correlations between properties. We are therefore motivated to develop strategies that allow these inhomogeneities to be more easily detected.
Results: Methods are described for constructing ensembles of
models within the context of a Mathematically Controlled Comparison.
A Density of Ratios Plot for a given systemic property is then
defined as follows: the
axis represents the value of the
systemic property in a reference model divided by the value in the
alternative model, and the
axis represents the value of the
systemic property in the reference model. Techniques involving
moving quantiles are introduced to generate secondary plots in which
correlations and inhomogeneities in correlations are more easily
detected. Several examples that illustrate the advantages of these
techniques are presented and discussed.
Contact: Savageau{at}umich.edu
* To whom correspondence should be addressed.
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