DC-ATLAS: a systems biology resource to dissect receptor specific signal transduction in dendritic cells
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,...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Cavalieri, Duccio [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2010 |
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| Schlagwörter: |
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| Anmerkung: |
© Cavalieri et al. 2010 |
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| Übergeordnetes Werk: |
Enthalten in: Immunome research - London : BioMed Central, 2005, 6(2010), 1 vom: 19. Nov. |
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| Übergeordnetes Werk: |
volume:6 ; year:2010 ; number:1 ; day:19 ; month:11 |
| Links: |
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| DOI / URN: |
10.1186/1745-7580-6-10 |
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| Katalog-ID: |
SPR029353033 |
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| 520 | |a 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 DC-ATLAS 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. | ||
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| 650 | 4 | |a System Biology Approach |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Outcome Module |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Signal Transduction Module |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Rivero, Damariz |4 aut | |
| 700 | 1 | |a Beltrame, Luca |4 aut | |
| 700 | 1 | |a Buschow, Sonja I |4 aut | |
| 700 | 1 | |a Calura, Enrica |4 aut | |
| 700 | 1 | |a Rizzetto, Lisa |4 aut | |
| 700 | 1 | |a Gessani, Sandra |4 aut | |
| 700 | 1 | |a Gauzzi, Maria C |4 aut | |
| 700 | 1 | |a Reith, Walter |4 aut | |
| 700 | 1 | |a Baur, Andreas |4 aut | |
| 700 | 1 | |a Bonaiuti, Roberto |4 aut | |
| 700 | 1 | |a Brandizi, Marco |4 aut | |
| 700 | 1 | |a De Filippo, Carlotta |4 aut | |
| 700 | 1 | |a D'Oro, Ugo |4 aut | |
| 700 | 1 | |a Draghici, Sorin |4 aut | |
| 700 | 1 | |a Dunand-Sauthier, Isabelle |4 aut | |
| 700 | 1 | |a Gatti, Evelina |4 aut | |
| 700 | 1 | |a Granucci, Francesca |4 aut | |
| 700 | 1 | |a Gündel, Michaela |4 aut | |
| 700 | 1 | |a Kramer, Matthijs |4 aut | |
| 700 | 1 | |a Kuka, Mirela |4 aut | |
| 700 | 1 | |a Lanyi, Arpad |4 aut | |
| 700 | 1 | |a Melief, Cornelis JM |4 aut | |
| 700 | 1 | |a van Montfoort, Nadine |4 aut | |
| 700 | 1 | |a Ostuni, Renato |4 aut | |
| 700 | 1 | |a Pierre, Philippe |4 aut | |
| 700 | 1 | |a Popovici, Razvan |4 aut | |
| 700 | 1 | |a Rajnavolgyi, Eva |4 aut | |
| 700 | 1 | |a Schierer, Stephan |4 aut | |
| 700 | 1 | |a Schuler, Gerold |4 aut | |
| 700 | 1 | |a Soumelis, Vassili |4 aut | |
| 700 | 1 | |a Splendiani, Andrea |4 aut | |
| 700 | 1 | |a Stefanini, Irene |4 aut | |
| 700 | 1 | |a Torcia, Maria G |4 aut | |
| 700 | 1 | |a Zanoni, Ivan |4 aut | |
| 700 | 1 | |a Zollinger, Raphael |4 aut | |
| 700 | 1 | |a Figdor, Carl G |4 aut | |
| 700 | 1 | |a Austyn, Jonathan M |4 aut | |
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10.1186/1745-7580-6-10 doi (DE-627)SPR029353033 (SPR)1745-7580-6-10-e DE-627 ger DE-627 rakwb eng Cavalieri, Duccio verfasserin aut DC-ATLAS: a systems biology resource to dissect receptor specific signal transduction in dendritic cells 2010 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Cavalieri et al. 2010 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 DC-ATLAS 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. Modular Structure (dpeaa)DE-He213 Pathway Database (dpeaa)DE-He213 System Biology Approach (dpeaa)DE-He213 Outcome Module (dpeaa)DE-He213 Signal Transduction Module (dpeaa)DE-He213 Rivero, Damariz aut Beltrame, Luca aut Buschow, Sonja I aut Calura, Enrica aut Rizzetto, Lisa aut Gessani, Sandra aut Gauzzi, Maria C aut Reith, Walter aut Baur, Andreas aut Bonaiuti, Roberto aut Brandizi, Marco aut De Filippo, Carlotta aut D'Oro, Ugo aut Draghici, Sorin aut Dunand-Sauthier, Isabelle aut Gatti, Evelina aut Granucci, Francesca aut Gündel, Michaela aut Kramer, Matthijs aut Kuka, Mirela aut Lanyi, Arpad aut Melief, Cornelis JM aut van Montfoort, Nadine aut Ostuni, Renato aut Pierre, Philippe aut Popovici, Razvan aut Rajnavolgyi, Eva aut Schierer, Stephan aut Schuler, Gerold aut Soumelis, Vassili aut Splendiani, Andrea aut Stefanini, Irene aut Torcia, Maria G aut Zanoni, Ivan aut Zollinger, Raphael aut Figdor, Carl G aut Austyn, Jonathan M aut Enthalten in Immunome research London : BioMed Central, 2005 6(2010), 1 vom: 19. Nov. (DE-627)500635749 (DE-600)2205002-4 1745-7580 nnns volume:6 year:2010 number:1 day:19 month:11 https://dx.doi.org/10.1186/1745-7580-6-10 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 6 2010 1 19 11 |
| spelling |
10.1186/1745-7580-6-10 doi (DE-627)SPR029353033 (SPR)1745-7580-6-10-e DE-627 ger DE-627 rakwb eng Cavalieri, Duccio verfasserin aut DC-ATLAS: a systems biology resource to dissect receptor specific signal transduction in dendritic cells 2010 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Cavalieri et al. 2010 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 DC-ATLAS 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. Modular Structure (dpeaa)DE-He213 Pathway Database (dpeaa)DE-He213 System Biology Approach (dpeaa)DE-He213 Outcome Module (dpeaa)DE-He213 Signal Transduction Module (dpeaa)DE-He213 Rivero, Damariz aut Beltrame, Luca aut Buschow, Sonja I aut Calura, Enrica aut Rizzetto, Lisa aut Gessani, Sandra aut Gauzzi, Maria C aut Reith, Walter aut Baur, Andreas aut Bonaiuti, Roberto aut Brandizi, Marco aut De Filippo, Carlotta aut D'Oro, Ugo aut Draghici, Sorin aut Dunand-Sauthier, Isabelle aut Gatti, Evelina aut Granucci, Francesca aut Gündel, Michaela aut Kramer, Matthijs aut Kuka, Mirela aut Lanyi, Arpad aut Melief, Cornelis JM aut van Montfoort, Nadine aut Ostuni, Renato aut Pierre, Philippe aut Popovici, Razvan aut Rajnavolgyi, Eva aut Schierer, Stephan aut Schuler, Gerold aut Soumelis, Vassili aut Splendiani, Andrea aut Stefanini, Irene aut Torcia, Maria G aut Zanoni, Ivan aut Zollinger, Raphael aut Figdor, Carl G aut Austyn, Jonathan M aut Enthalten in Immunome research London : BioMed Central, 2005 6(2010), 1 vom: 19. Nov. (DE-627)500635749 (DE-600)2205002-4 1745-7580 nnns volume:6 year:2010 number:1 day:19 month:11 https://dx.doi.org/10.1186/1745-7580-6-10 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 6 2010 1 19 11 |
| allfields_unstemmed |
10.1186/1745-7580-6-10 doi (DE-627)SPR029353033 (SPR)1745-7580-6-10-e DE-627 ger DE-627 rakwb eng Cavalieri, Duccio verfasserin aut DC-ATLAS: a systems biology resource to dissect receptor specific signal transduction in dendritic cells 2010 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Cavalieri et al. 2010 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 DC-ATLAS 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. Modular Structure (dpeaa)DE-He213 Pathway Database (dpeaa)DE-He213 System Biology Approach (dpeaa)DE-He213 Outcome Module (dpeaa)DE-He213 Signal Transduction Module (dpeaa)DE-He213 Rivero, Damariz aut Beltrame, Luca aut Buschow, Sonja I aut Calura, Enrica aut Rizzetto, Lisa aut Gessani, Sandra aut Gauzzi, Maria C aut Reith, Walter aut Baur, Andreas aut Bonaiuti, Roberto aut Brandizi, Marco aut De Filippo, Carlotta aut D'Oro, Ugo aut Draghici, Sorin aut Dunand-Sauthier, Isabelle aut Gatti, Evelina aut Granucci, Francesca aut Gündel, Michaela aut Kramer, Matthijs aut Kuka, Mirela aut Lanyi, Arpad aut Melief, Cornelis JM aut van Montfoort, Nadine aut Ostuni, Renato aut Pierre, Philippe aut Popovici, Razvan aut Rajnavolgyi, Eva aut Schierer, Stephan aut Schuler, Gerold aut Soumelis, Vassili aut Splendiani, Andrea aut Stefanini, Irene aut Torcia, Maria G aut Zanoni, Ivan aut Zollinger, Raphael aut Figdor, Carl G aut Austyn, Jonathan M aut Enthalten in Immunome research London : BioMed Central, 2005 6(2010), 1 vom: 19. Nov. (DE-627)500635749 (DE-600)2205002-4 1745-7580 nnns volume:6 year:2010 number:1 day:19 month:11 https://dx.doi.org/10.1186/1745-7580-6-10 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 6 2010 1 19 11 |
| allfieldsGer |
10.1186/1745-7580-6-10 doi (DE-627)SPR029353033 (SPR)1745-7580-6-10-e DE-627 ger DE-627 rakwb eng Cavalieri, Duccio verfasserin aut DC-ATLAS: a systems biology resource to dissect receptor specific signal transduction in dendritic cells 2010 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Cavalieri et al. 2010 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 DC-ATLAS 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. Modular Structure (dpeaa)DE-He213 Pathway Database (dpeaa)DE-He213 System Biology Approach (dpeaa)DE-He213 Outcome Module (dpeaa)DE-He213 Signal Transduction Module (dpeaa)DE-He213 Rivero, Damariz aut Beltrame, Luca aut Buschow, Sonja I aut Calura, Enrica aut Rizzetto, Lisa aut Gessani, Sandra aut Gauzzi, Maria C aut Reith, Walter aut Baur, Andreas aut Bonaiuti, Roberto aut Brandizi, Marco aut De Filippo, Carlotta aut D'Oro, Ugo aut Draghici, Sorin aut Dunand-Sauthier, Isabelle aut Gatti, Evelina aut Granucci, Francesca aut Gündel, Michaela aut Kramer, Matthijs aut Kuka, Mirela aut Lanyi, Arpad aut Melief, Cornelis JM aut van Montfoort, Nadine aut Ostuni, Renato aut Pierre, Philippe aut Popovici, Razvan aut Rajnavolgyi, Eva aut Schierer, Stephan aut Schuler, Gerold aut Soumelis, Vassili aut Splendiani, Andrea aut Stefanini, Irene aut Torcia, Maria G aut Zanoni, Ivan aut Zollinger, Raphael aut Figdor, Carl G aut Austyn, Jonathan M aut Enthalten in Immunome research London : BioMed Central, 2005 6(2010), 1 vom: 19. Nov. (DE-627)500635749 (DE-600)2205002-4 1745-7580 nnns volume:6 year:2010 number:1 day:19 month:11 https://dx.doi.org/10.1186/1745-7580-6-10 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 6 2010 1 19 11 |
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10.1186/1745-7580-6-10 doi (DE-627)SPR029353033 (SPR)1745-7580-6-10-e DE-627 ger DE-627 rakwb eng Cavalieri, Duccio verfasserin aut DC-ATLAS: a systems biology resource to dissect receptor specific signal transduction in dendritic cells 2010 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Cavalieri et al. 2010 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 DC-ATLAS 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. Modular Structure (dpeaa)DE-He213 Pathway Database (dpeaa)DE-He213 System Biology Approach (dpeaa)DE-He213 Outcome Module (dpeaa)DE-He213 Signal Transduction Module (dpeaa)DE-He213 Rivero, Damariz aut Beltrame, Luca aut Buschow, Sonja I aut Calura, Enrica aut Rizzetto, Lisa aut Gessani, Sandra aut Gauzzi, Maria C aut Reith, Walter aut Baur, Andreas aut Bonaiuti, Roberto aut Brandizi, Marco aut De Filippo, Carlotta aut D'Oro, Ugo aut Draghici, Sorin aut Dunand-Sauthier, Isabelle aut Gatti, Evelina aut Granucci, Francesca aut Gündel, Michaela aut Kramer, Matthijs aut Kuka, Mirela aut Lanyi, Arpad aut Melief, Cornelis JM aut van Montfoort, Nadine aut Ostuni, Renato aut Pierre, Philippe aut Popovici, Razvan aut Rajnavolgyi, Eva aut Schierer, Stephan aut Schuler, Gerold aut Soumelis, Vassili aut Splendiani, Andrea aut Stefanini, Irene aut Torcia, Maria G aut Zanoni, Ivan aut Zollinger, Raphael aut Figdor, Carl G aut Austyn, Jonathan M aut Enthalten in Immunome research London : BioMed Central, 2005 6(2010), 1 vom: 19. Nov. (DE-627)500635749 (DE-600)2205002-4 1745-7580 nnns volume:6 year:2010 number:1 day:19 month:11 https://dx.doi.org/10.1186/1745-7580-6-10 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 6 2010 1 19 11 |
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Cavalieri, Duccio Rivero, Damariz Beltrame, Luca Buschow, Sonja I Calura, Enrica Rizzetto, Lisa Gessani, Sandra Gauzzi, Maria C Reith, Walter Baur, Andreas Bonaiuti, Roberto Brandizi, Marco De Filippo, Carlotta D'Oro, Ugo Draghici, Sorin Dunand-Sauthier, Isabelle Gatti, Evelina Granucci, Francesca Gündel, Michaela Kramer, Matthijs Kuka, Mirela Lanyi, Arpad Melief, Cornelis JM van Montfoort, Nadine Ostuni, Renato Pierre, Philippe Popovici, Razvan Rajnavolgyi, Eva Schierer, Stephan Schuler, Gerold Soumelis, Vassili Splendiani, Andrea Stefanini, Irene Torcia, Maria G Zanoni, Ivan Zollinger, Raphael Figdor, Carl G Austyn, Jonathan M |
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dc-atlas: a systems biology resource to dissect receptor specific signal transduction in dendritic cells |
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DC-ATLAS: a systems biology resource to dissect receptor specific signal transduction in dendritic cells |
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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 DC-ATLAS 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. © Cavalieri et al. 2010 |
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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 DC-ATLAS 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. © Cavalieri et al. 2010 |
| abstract_unstemmed |
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 DC-ATLAS 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. © Cavalieri et al. 2010 |
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Rivero, Damariz Beltrame, Luca Buschow, Sonja I Calura, Enrica Rizzetto, Lisa Gessani, Sandra Gauzzi, Maria C Reith, Walter Baur, Andreas Bonaiuti, Roberto Brandizi, Marco De Filippo, Carlotta D'Oro, Ugo Draghici, Sorin Dunand-Sauthier, Isabelle Gatti, Evelina Granucci, Francesca Gündel, Michaela Kramer, Matthijs Kuka, Mirela Lanyi, Arpad Melief, Cornelis JM van Montfoort, Nadine Ostuni, Renato Pierre, Philippe Popovici, Razvan Rajnavolgyi, Eva Schierer, Stephan Schuler, Gerold Soumelis, Vassili Splendiani, Andrea Stefanini, Irene Torcia, Maria G Zanoni, Ivan Zollinger, Raphael Figdor, Carl G Austyn, Jonathan M |
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