Parenclitic networks: Uncovering new functions in biological data

Massimiliano Zanin, Joaquín Medina Alcazar, Jesus Vicente Carbajosa, Marcela Gomez Paez, David Papo, Pedro Sousa, Ernestina Menasalvas, Stefano Boccaletti

Research output: Contribution to journalArticle

8 Citations (Scopus)

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.
Original languageEnglish
Article number05112
JournalScientific Reports
Volume4
DOIs
Publication statusPublished - 29 May 2014

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    Zanin, M., Alcazar, J. M., Carbajosa, J. V., Paez, M. G., Papo, D., Sousa, P., ... Boccaletti, S. (2014). Parenclitic networks: Uncovering new functions in biological data. Scientific Reports, 4, [05112]. https://doi.org/10.1038/srep05112