Provenance

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charles.hoyt@scai.fraunhofer.de at 2018-04-03 15:17:40
Authors
Causal Biological Networks Database
Contact
CausalBiologicalNetworks.RD@pmi.com
Description
The NK Signaling network depicts the causal mechanisms involved in NK cell activation and the induction of target cell cytolysis in response to upstream signals, including interleukins, TGFB1, IFNs and ITGB2.
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
48
Number Edges
77
Number Components
15
Network Density
0.0341312
Average Degree
1.60417
Number Citations
47
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
BEL Framework Large Corpus Document v20170611 58%
Selventa Protein Families Definitions v20150611 40%
Dendritic Cell Signaling-2.0-Rn v2.0 38%
Neutrophil Signaling-2.0-Rn v2.0 35%
Macrophage Signaling-2.0-Rn v2.0 33%
Th1-Th2 Signaling-2.0-Rn v2.0 29%
BEL Framework Small Corpus Document v20150611 25%
Growth Factor-2.0-Rn v2.0 25%
Th17 Signaling-2.0-Rn v2.0 25%
NK Signaling-2.0-Hs v2.0 23%

Sample Edges

p(HGNC:IFNA1) increases act(p(SFAM:"STAT5 Family"), ma(tscript))

IL-2 induced less STAT1 alpha activation and IFN-alpha induced greater STAT5 activation in NK3.3 cells compared with preactivated primary NK cells. PubMed:8683106

p(HGNC:IFNA1) increases act(p(SFAM:"STAT5 Family"), ma(tscript))

(see introduction) STAT3 and STAT5 are strongly activated by type I IFNs PubMed:15634877

bp(GOBP:"natural killer cell activation") increases bp(GOBP:cytolysis)

Slaying the Trojan horse: Natural killer cells exhibit robust anti-HIV-1 antibody-dependent activation and cytolysis against allogeneic T-cells. We found that NK cells are robustly activated in an anti-HIV-1 Ab-dependent manner against allogeneic targets, and that tested target cells are subject to Ab-dependent cytolysis. Other:25320293

act(p(SFAM:"STAT5 Family"), ma(tscript)) increases bp(GOBP:"natural killer cell differentiation")

Blocking the Axl-Gas6 interaction with a soluble Axl fusion protein (Axl-Fc) or the vitamin K inhibitor warfarin significantly diminished the absolute number and percentage of CD3(-)CD56(+) NK cells derived from human CD34(+) HPCs cultured in the presence of IL-15, probably resulting in part from reduced phosphorylation of STAT5 PubMed:18840707

act(p(RGD:Map2k1), ma(kin)) directlyIncreases act(p(RGD:Mapk3), ma(kin))

To elucidate the role of MAPKs in keratinocyte differentiation, activation of ERK, JNK, and p38 in response to stimulation with extracellular calcium was analyzed. We provide evidence that calcium-induced differentiation of keratinocytes is associated with rapid and transient activation of the Raf/MEK/ERK pathway. Stimulation of keratinocytes with extracellular calcium resulted in activation of Raf isozymes and their downstream effector ERK within 10-15 min, but did not increase JNK or p38 activity PubMed:11018025

Sample Nodes

p(RGD:Mapk3)

In-Edges: 173 | Out-Edges: 60 | Explore Neighborhood | Download JSON

p(RGD:Ifng)

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

p(RGD:Mapk1)

In-Edges: 233 | Out-Edges: 67 | Explore Neighborhood | Download JSON

p(RGD:Cx3cl1)

In-Edges: 5 | Out-Edges: 6 | Explore Neighborhood | Download JSON

p(RGD:Pak1)

In-Edges: 3 | Out-Edges: 0 | 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.