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charles.hoyt@scai.fraunhofer.de at 2018-04-03 15:19:01
Authors
Causal Biological Networks Database
Contact
CausalBiologicalNetworks.RD@pmi.com
Description
The Th1/Th2 Signaling network depicts the causal mechanisms that are activated in T helper 1 (Th1) cells following engagement with macrophages including pathways related to the STAT4 and T-bet transcription factors leading to Th1-specific differentiation as well as the causal mechanisms that are activated in T helper 2 (Th2) cells following engagement primarily with B-cells including pathways related to the STAT6 and GATA transcription factors leading to Th2-specific differentiation. The network also encompasses the chemokine pathways involved in mediating T-cell recruitment to compromised lung tissue during COPD development and Th1-produced cytokines that activate cytotoxic T-cells, natural killer cells and macrophages and Th2-produced cytokines that activate B cells, eosinophils and suppress macrophage activation.\u003c/p\u003e\n\u003ch2\u003eJamboree Review Focus\u003c/h2\u003e\n\u003cp\u003eLung memory CD4+ T cell signaling and T-helper cell interaction with other immune cells including T-helper and B cell CD40L-CD40 interaction and NK and Tc activation by Th cells. Reviewed during Jamboree2014. Reviewed during Jamboree2015
License
Please cite: - www.causalbionet.com - https://bionet.sbvimprover.com as well as any relevant publications. The sbv IMPROVER project, the website and the Symposia are part of a collaborative project designed to enable scientists to learn about and contribute to the development of a new crowd sourcing method for verification of scientific data and results. The current challenges, website and biological network models were developed and are maintained as part of a collaboration among Selventa, OrangeBus and ADS. The project is led and funded by Philip Morris International. For more information on the focus of Philip Morris International’s research, please visit www.pmi.com.
Number Nodes
108
Number Edges
253
Number Components
10
Network Density
0.0218934
Average Degree
2.34259
Number Citations
134
Number BEL Errors
0

Content Statistics

Network Overlap

The node-based overlap between this network and other networks is calculated as the Szymkiewicz-Simpson coefficient of their respective nodes. Up to the top 10 are shown below.

Network Overlap
Th17 Signaling-2.0-Rn v2.0 51%
Treg Signaling-2.0-Rn v2.0 40%
Cytotoxic T-cell Signaling-2.0-Rn v2.0 36%
BEL Framework Large Corpus Document v20170611 32%
NK Signaling-2.0-Rn v2.0 29%
Dendritic Cell Signaling-2.0-Rn v2.0 27%
Th1-Th2 Signaling-2.0-Hs v2.0 23%
Th1-Th2 Signaling-2.0-Mm v2.0 23%
Notch-2.0-Rn v2.0 21%
Mast cell activation-2.0-Rn v2.0 20%

Sample Edges

bp(GOBP:"T-helper 2 cell differentiation") subProcessOf bp(GOBP:"type 2 immune response")

accessed 2015-07-30, relationship = part_of Online Resource:geneontology.org

complex(GOCC:"gamma-secretase complex") increases p(SFAM:"NOTCH Family")

In vitro, gamma-secretase inhibitors extinguished expression of Notch, interferon-gamma and Tbx21 in TH1-polarized CD4+ cells, whereas ectopic expression of activated Notch1 restored Tbx21 transcription. PubMed:15991363

act(p(HGNC:TRB)) increases bp(GOBP:"T cell activation")

The four T cell receptor genes (Tcra, Tcrb, Tcrg, Tcrd) are assembled by V(D)J recombination according to distinct programs during intrathymic T cell development. These programs depend on genetic factors, including gene segment order and recombination signal sequences. They also depend on epigenetic factors. Regulated changes in chromatin structure, directed by enhancers and promoter, can modify the availability of recombination signal sequences to the RAG recombinase. Regulated changes in locus conformation may control the synapsis of distant recombination signal sequences, and regulated changes in subnuclear positioning may influence locus recombination events by unknown mechanisms. Together these influences may explain the ordered activation and inactivation of T cell receptor locus recombination events and the phenomenon of Tcrb allelic exclusion. PubMed:19362456

Sample Nodes

p(RGD:Ccl3)

In-Edges: 11 | Out-Edges: 19 | Explore Neighborhood | Download JSON

bp(GOBP:"inflammatory response")

In-Edges: 792 | Out-Edges: 404 | Children: 3 | Explore Neighborhood | Download JSON

p(RGD:Ifng)

In-Edges: 45 | Out-Edges: 79 | Explore Neighborhood | Download JSON

p(RGD:Il6)

In-Edges: 166 | Out-Edges: 99 | Explore Neighborhood | Download JSON

About

BEL Commons is developed and maintained in an academic capacity by Charles Tapley Hoyt and Daniel Domingo-Fernández at the Fraunhofer SCAI Department of Bioinformatics with support from the IMI project, AETIONOMY. It is built on top of the open source project, PyBEL. Please feel free to contact us here to give us feedback or report any issues.