Parenclitic networks: uncovering new functions in biological data (Articolo in rivista)

Type
Label
  • Parenclitic networks: uncovering new functions in biological data (Articolo in rivista) (literal)
Anno
  • 2014-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1038/srep05112 (literal)
Alternative label
  • Massimiliano Zanin (1,2); Joaquín Medina Alcazar (3); Jesus Vicente Carbajosa (3); Marcela Gomez Paez (3); David Papo (4); Pedro Sousa (1); Ernestina Menasalvas (4); Stefano Boccaletti (5) (2014)
    Parenclitic networks: uncovering new functions in biological data
    in Scientific reports (Nature Publishing Group)
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Massimiliano Zanin (1,2); Joaquín Medina Alcazar (3); Jesus Vicente Carbajosa (3); Marcela Gomez Paez (3); David Papo (4); Pedro Sousa (1); Ernestina Menasalvas (4); Stefano Boccaletti (5) (literal)
Pagina inizio
  • 5112 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
  • http://www.nature.com/srep/2014/140529/srep05112/full/srep05112.html (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
  • 4 (literal)
Rivista
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#pagineTotali
  • 6 (literal)
Note
  • ISI Web of Science (WOS) (literal)
  • Scopu (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • (1) Faculdade de Ciências e Tecnologia, Departamento de Engenharia Electrotécnica, Universidade Nova de Lisboa, Lisboa, Portugal (2) Innaxis Foundation & Research Institute, José Ortega y Gasset 20, 28006, Madrid, Spain (3) Centro de Biotecnología y Genómica de Plantas, Universidad Politécnica de Madrid, 28223 Pozuelo de Alarcón, Madrid, Spain (4) Center for Biomedical Technology, Universidad Politécnica de Madrid, 28223 Pozuelo de Alarcón, Madrid, Spain (5) CNR- Institute of Complex Systems, Via Madonna del Piano 10, 50019 Sesto Fiorentino, Florence, Italy (literal)
Titolo
  • Parenclitic networks: uncovering new functions in biological data (literal)
Abstract
  • We introduce a novel method to represent time independent, scalar data sets as complex networks. We apply our method to investigate gene expression in the response to osmotic stress of Arabidopsis thaliana. In the proposed network representation, the most important genes for the plant response turn out to be the nodes with highest centrality in appropriately reconstructed networks. We also performed a target experiment, in which the predicted genes were artificially induced one by one, and the growth of the corresponding phenotypes compared to that of the wild-type. The joint application of the network reconstruction method and of the in vivo experiments allowed identifying 15 previously unknown key genes, and provided models of their mutual relationships. This novel representation extends the use of graph theory to data sets hitherto considered outside of the realm of its application, vastly simplifying the characterization of their underlying structure. (literal)
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