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Using Ontologies to Represent Immunological Networks Lindsay G. Cowell, Anne Lieberman, Anna Maria Masci Duke University Center for Computational Immunology.

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Presentation on theme: "Using Ontologies to Represent Immunological Networks Lindsay G. Cowell, Anne Lieberman, Anna Maria Masci Duke University Center for Computational Immunology."— Presentation transcript:

1 Using Ontologies to Represent Immunological Networks Lindsay G. Cowell, Anne Lieberman, Anna Maria Masci Duke University Center for Computational Immunology

2 PeripherySecondary Lymphoid TissuePeriphery

3 molecular pattern recognition receptor binding signaling migration Periphery Secondary Lymphoid TissuePeriphery Cell Molecule maturation secretion cytokine chemokine adhesion molecule dendritic cell endothelial cell Process Ag processing Ag presentation MHC T cell activation TCR dendritic cell naïve T cell dendritic celldendritic cell memory T cell effector T cell T cell differentiation migration secretion chemokine receptor cytokine effector T cell chemokine CD69 CD44 CD25

4 PeripherySecondary Lymphoid TissuePeriphery Tightly regulated: expansion/suppression qualitatively different responses to different pathogens XXX

5 PeripherySecondary Lymphoid TissuePeriphery TLR2 IL-8 IL-10 IL-23p19 dendritic cell naïve CD4+ T cell TLR4 IL-12p70 IP-10 IFNb IL-15 CD4+ T helper cell Type 2 Type 1 IFNg TNFb IL-4 IL-5 IL-6 IL-10 IL-13 CD4+ T helper cell B cell macrophage

6 PeripherySecondary Lymphoid TissuePeriphery Multiple levels of granularity Temporal ordering of processes Modularity and transitioning between modules

7 Ligation of TLR2 expressed on dendritic cells induces secretion of IL-10. (Binding has participant (TLR2 part of dendritic cell) ) followed by (secretion has participant (dendritic cell and IL-10) )

8 RELATION TO TIME GRANULARITY CONTINUANTOCCURRENT INDEPENDENTDEPENDENT ORGAN AND ORGANISM Organism (NCBI Taxonomy?) Anatomical Entity (FMA, CARO) Organ Function (FMP, CPRO) Phenotypic Quality (PaTO) Organism-Level Process (GO) CELL AND CELLULAR COMPONENT Cell (CL) Cellular Component (FMA, GO) Cellular Function (GO) Cellular Process (GO) MOLECULE Molecule (ChEBI, SO, RnaO, PrO) Molecular Function (GO) Molecular Process (GO) Lymph node Spleen Macrophage B lymphocyte Phagocytosis Homing Antigen processing IL-12 TLR-4 Relation Ontology

9 CLGO BPPRORO Ligation of TLR2 expressed on dendritic cells induces secretion of IL-10. (Binding has participant (TLR2 part of dendritic cell)) followed by (secretion has participant (dendritic cell and IL-10))

10 Benefits to Using OBO Foundry Ontologies Utilize the ontologies’ hierarchies Interoperability with other databases and knowledge sources Principles of development improve consistency and reduce errors Underlying formalism supports long-term goal of computing over this information

11 TLR2 TIR domain has_part Dendritic cell has_part TLR2:TLR2 ligand binding TIR domain has_part TLR2 signaling has_lower_level_granularity TLR2-MyD88 binding TIR:TIR binding has_part followed_by

12 has_lower_level_granularity TLR2:MyD88 binding TLR2 has_participant LTA binding has_disposition TIR domain has_part TLR2:TLR2 ligand binding TIR:TIR binding process preceeded_by regulated_by has_output has_participant TLR2:MyD88 complex MyD88 has_participant

13 has_lower_level_granularity TLR2-MyD88 binding TLR2 has_participant TIR domain has_part TLR2:TLR2 ligand binding TIR-TIR binding preceeded_by has_output has_participant TLR2:MyD88 complex MyD88 has_participant TLR2:MyD88 complex – IRAK4 binding preceeded_by has_participant has_output has_participant IRAK4

14 has_lower_level_granularity TLR2-MyD88 binding TLR2 has_participant TIR domain has_part TLR2:TLR2 ligand binding TIR:TIR binding preceeded_by has_output has_participant TLR2:MyD88 complex MyD88 has_participant TLR2:MyD88 complex – IRAK4 binding preceeded_by has_participant has_output has_participant IRAK4 MyD88 – IRAK4 binding has_participant has_part has_lower_level_granularity

15 Acknowledgements Anna Maria Masci, Duke University Center for Computational Immunology Anne Lieberman, Duke University Center for Computational Immunology Barry Smith, University at Buffalo Fabian Neuhaus, NIST OBO Ontology Community (Alex Diehl, Jamie Lee, Onard Mejino, Chris Mungall, Richard Scheuermann, Alan Ruttenberg) Burroughs Wellcome Fund, NIAID - DAIT

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18 has_lower_level_granularity process continuant has_participant ability to participate in a process has_disposition continuant has_part process preceeded_by regulated_by amplified_by suppressed_by has_output has_agent initiated_by stopped_by continuant has_participant Types of regulated_by


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