title: Multiscale characterization of ageing and cancer progression by a novel network entropy measure.
abstract: We characterize different cell states, related to cancer and ageing phenotypes, by a measure of entropy of network ensembles, integrating gene expression profiling values and protein interaction network topology. In our case studies, network entropy, that by definition estimates the number of possible network instances satisfying the given constraints, can be interpreted as a measure of the "parameter space" available to the cell. Network entropy was able to characterize specific pathological conditions: normal versus cancer cells, primary tumours that developed metastasis or relapsed, and extreme longevity samples. Moreover, this approach has been applied at different scales, from whole network to specific subnetworks (biological pathways defined on a priori biological knowledge) and single nodes (genes), allowing a deeper understanding of the cell processes involved.
authors.affiliation: Department of Physics and Astronomy and INFN, Bologna University, Viale B. Pichat 6/2, 40127 Bologna, Italy. daniel.remondini@unibo.it.
authors.forename: Giulia
authors.initials: G
authors.lastname: Menichetti
authors.forename: Ginestra
authors.initials: G
authors.lastname: Bianconi
authors.forename: Gastone
authors.initials: G
authors.lastname: Castellani
authors.forename: Enrico
authors.initials: E
authors.lastname: Giampieri
authors.forename: Daniel
authors.initials: D
authors.lastname: Remondini
mesh_terms: D000375:Aging; D000465:Algorithms; D018450:Disease Progression; D019277:Entropy; D020869:Gene Expression Profiling; D006801:Humans; D008954:Models, Biological; D009369:Neoplasms / Q000378:metabolism* / Q000473:pathology; D060066:Protein Interaction Maps