Work

Entropy-Based Network Representation of the Individual Metabolic Phenotype

Year: 2016

Type: article

Abstract: We approach here the problem of defining and estimating the nature of the metabolite-metabolite association network underlying the human individual metabolic phenotype in healthy subjects. We retrieved significant associations using an entropy-based approach and a multiplex network formalism. We defined a significantly over-represented network formed by biologically interpretable metabolite modules. The entropy of the individual metabolic phenotype is also introduced and discussed.

Source: Journal of Proteome Research

DOI: 10.1021/acs.jproteome.6b00454

Authors: Edoardo Saccenti, Giulia Menichetti, Veronica Ghini, Daniel Remondini, Leonardo Tenori, Claudio Luchinat

Institutions: Wageningen University & Research, Istituto Nazionale di Fisica Nucleare, Sezione di Bologna, University of Bologna, University of Florence

Language: English

Topic: Bioinformatics and Genomic Networks

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: green

Funders: Ministero dell’Istruzione, dell’Università e della Ricerca, Fondazione Umberto Veronesi, Seventh Framework Programme

Awards: G1953138573, G5307338832, G7398942085