Background: The advent of Systems Biology has been accompanied by the blooming of pathway databases. Currently pathways are defined generically with respect to the organ or cell type where a reaction takes place. The cell type specificity of the reactions is the foundation of immunological research, and capturing this specificity is of paramount importance when using pathway-based analyses to decipher complex immunological datasets. Here, we present DC-ATLAS, a novel and versatile resource for the interpretation of high-throughput data generated perturbing the signaling network of dendritic cells (DCs). Results: Pathways are annotated using a novel data model, the Biological Connection Markup Language (BCML), a SBGN-compliant data format developed to store the large amount of information collected. The application of DCATLAS to pathway-based analysis of the transcriptional program of DCs stimulated with agonists of the toll-like receptor family allows an integrated description of the flow of information from the cellular sensors to the functional outcome, capturing the temporal series of activation events by grouping sets of reactions that occur at different time points in well-defined functional modules. Conclusions: The initiative significantly improves our understanding of DC biology and regulatory networks. Developing a systems biology approach for immune system holds the promise of translating knowledge on the immune system into more successful immunotherapy strategies.

DC-ATLAS: a systems biology resource to dissect receptor specific signal transduction in dendritic cells / D. Cavalieri; D. Rivero; L. Beltrame; S. I. Buschow; E. Calura; L. Rizzetto; S. Gessani; M. C. Gauzzi; W. Reith; A. Baur; R. Bonaiuti; M. Brandizi; C. De Filippo; U. D'Oro; S. Draghici; I. Dunand-Sauthier; E. Gatti; F. Granucci; M. Gündel; M. Kramer; M. Kuka; A. Lanyi; C. J. Melief; N. van Montfoort; R. Ostuni; P. Pierre; R. Popovici; E. Rajnavolgyi; S. Schierer; G. Schuler; V. Soumelis; A. Splendiani; I. Stefanini; M. G. Torcia; I. Zanoni; R. Zollinger; C. G. Figdor; J. M. Austyn. - In: IMMUNOME RESEARCH. - ISSN 1745-7580. - ELETTRONICO. - 6:(2010), pp. 0-0. [10.1186/1745-7580-6-10]

DC-ATLAS: a systems biology resource to dissect receptor specific signal transduction in dendritic cells.

CAVALIERI, DUCCIO;BELTRAME, LUCA;RIZZETTO, LISA;BONAIUTI, ROBERTO;DE FILIPPO, CARLOTTA;STEFANINI, IRENE;TORCIA, MARIA;
2010

Abstract

Background: The advent of Systems Biology has been accompanied by the blooming of pathway databases. Currently pathways are defined generically with respect to the organ or cell type where a reaction takes place. The cell type specificity of the reactions is the foundation of immunological research, and capturing this specificity is of paramount importance when using pathway-based analyses to decipher complex immunological datasets. Here, we present DC-ATLAS, a novel and versatile resource for the interpretation of high-throughput data generated perturbing the signaling network of dendritic cells (DCs). Results: Pathways are annotated using a novel data model, the Biological Connection Markup Language (BCML), a SBGN-compliant data format developed to store the large amount of information collected. The application of DCATLAS to pathway-based analysis of the transcriptional program of DCs stimulated with agonists of the toll-like receptor family allows an integrated description of the flow of information from the cellular sensors to the functional outcome, capturing the temporal series of activation events by grouping sets of reactions that occur at different time points in well-defined functional modules. Conclusions: The initiative significantly improves our understanding of DC biology and regulatory networks. Developing a systems biology approach for immune system holds the promise of translating knowledge on the immune system into more successful immunotherapy strategies.
2010
6
0
0
D. Cavalieri; D. Rivero; L. Beltrame; S. I. Buschow; E. Calura; L. Rizzetto; S. Gessani; M. C. Gauzzi; W. Reith; A. Baur; R. Bonaiuti; M. Brandizi; C. De Filippo; U. D'Oro; S. Draghici; I. Dunand-Sauthier; E. Gatti; F. Granucci; M. Gündel; M. Kramer; M. Kuka; A. Lanyi; C. J. Melief; N. van Montfoort; R. Ostuni; P. Pierre; R. Popovici; E. Rajnavolgyi; S. Schierer; G. Schuler; V. Soumelis; A. Splendiani; I. Stefanini; M. G. Torcia; I. Zanoni; R. Zollinger; C. G. Figdor; J. M. Austyn
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/605555
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