Consiglio Nazionale delle Ricerche

Tipo di prodottoArticolo in rivista
TitoloAnalyses of antigen dependency networks unveil immune system reorganization between birth and adulthood
Anno di pubblicazione2011
Formato
  • Elettronico
  • Cartaceo
Autore/iAsaf Madi (1,2); Dror Y. Kenett (1); Sharron Bransburg-Zabary (1,2); Yifat Merbl (3); Francisco J. Quintana (3); Stefano Boccaletti (1,4); Alfred I. Tauber (5); Irun R. Cohen (3); Eshel Ben-Jacob (1,6)
Affiliazioni autori(1) School of Physics and Astronomy, Tel Aviv University, 69978 Tel Aviv, Israel (2) Faculty of Medicine, Tel Aviv University, 69978 Tel Aviv, Israel 3Department of Immunology, Weizmann Institute of Science, Rehovot 76100, Israel (4) CNR, Institute of Complex Systems, Florence, Italy and the Italian Embassy in Israel, Israel (5) School of Medicine, Boston University, Boston, Massachusetts 02215, USA (6) The Center for Theoretical and Biological Physics, University of California San Diego, La Jolla, California 92093, USA
Autori CNR e affiliazioni
  • STEFANO BOCCALETTI
Lingua/e
  • inglese
AbstractMuch effort has been devoted to assess the importance of nodes in complex biological networks (such as gene transcriptional regulatory networks, protein interaction networks, and neural networks). Examples of commonly used measures of node importance include node degree, node centrality, and node vulnerability score (the effect of the node deletion on the network efficiency). Here, we present a new approach to compute and investigate the mutual dependencies between network nodes from the matrices of node-node correlations. To this end, we first define the dependency of node i on node j (or the influence of node j on node i), D(i, j) as the average over all nodes k of the difference between the i-k correlation and the partial correlations between these nodes with respect to node j. Note that the dependencies, D(i, j) define a directed weighted matrix, since, in general, D(i, j) differs from D(j, i). For this reason, many of the commonly used measures of node importance, such as node centrality, cannot be used. Hence, to assess the node importance of the dependency networks, we define the system level influence (SLI) of antigen j, SLI(j) as the sum of the influence of j on all other antigens i. Next, we define the system level influence or the influence score of antigen j, SLI(j) as the sum of D(i, j) over all nodes i. We introduce the new approach and demonstrate that it can unveil important biological information in the context of the immune system. More specifically, we investigated antigen dependency networks computed from antigen microarray data of autoantibody reactivity of IgM and IgG isotypes present in the sera of ten mothers and their newborns. We found that the analysis was able to unveil that there is only a subset of antigens that have high influence scores (SLI) common both to the mothers and newborns. Networks comparison in terms of modularity (using the Newman's algorithm) and of topology (measured by the divergence rate) revealed that, at birth, the IgG networks exhibit a more profound global reorganization while the IgM networks exhibit a more profound local reorganization. During immune system development, the modularity of the IgG network increases and becomes comparable to that of the IgM networks at adulthood. We also found the existence of several conserved IgG and IgM network motifs between the maternal and newborns networks, which might retain network information as our immune system develops. If correct, these findings provide a convincing demonstration of the effectiveness of the new approach to unveil most significant biological information. Whereas we have introduced the new approach within the context of the immune system, it is expected to be effective in the studies of other complex biological social, financial, and manmade networks.
Lingua abstractinglese
Altro abstract-
Lingua altro abstract-
Pagine da016109
Pagine a-
Pagine totali11
RivistaChaos (Woodbury N.Y.)
Attiva dal 1991
Editore: American Institute of Physics, - Woodbury, NY
Paese di pubblicazione: Stati Uniti d'America
Lingua: inglese
ISSN: 1054-1500
Titolo chiave: Chaos (Woodbury N.Y.)
Titolo proprio: Chaos. (Woodbury N.Y.)
Titolo abbreviato: Chaos (Woodbury N.Y.)
Numero volume della rivista211
Fascicolo della rivista1
DOI10.1063/1.3543800
Verificato da refereeSì: Internazionale
Stato della pubblicazionePublished version
Indicizzazione (in banche dati controllate)
  • ISI Web of Science (WOS) (Codice:000289149100037)
  • Scopus (Codice:2-s2.0-79953290372)
Parole chiaveCOMPLEX NETWORKS, HIERARCHICAL STRUCTURE, COMMUNITY STRUCTURE, INFORMATION, MODULES
Link (URL, URI)http://link.aip.org/link/doi/10.1063/1.3543800
Titolo parallelo-
Licenza-
Scadenza embargo-
Data di accettazione29/12/2010
Note/Altre informazioniPublished online 29 marzo 2011.
Strutture CNR
  • ISC — ISC - Sede secondaria di Firenze - Sesto Fiorentino
Moduli/Attività/Sottoprogetti CNR
  • MD.P02.017.001 : comportamento dinamico di sistemi complessi
Progetti Europei-
Allegati
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