Provenance

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charles.hoyt@scai.fraunhofer.de at 2018-04-03 15:17:08
Authors
Causal Biological Networks Database
Contact
CausalBiologicalNetworks.RD@pmi.com
Description
The Macrophage Signaling describes the causal mechanisms in pathways related to the recruitment of macrophages to sites of tissue injury, differentiation of macrophages from hematopoietic progenitors and macrophage activation in response to environmental cues. The network also includes cell surface receptors and signaling pathways involved in macrophage efferocytosis, a process known to be largely inhibited during COPD development.\nReviewed during Jamboree2014\nReviewed 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
174
Number Edges
526
Number Components
29
Network Density
0.0174739
Average Degree
3.02299
Number Citations
376
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 55%
Tissue Damage-2.0-Rn v2.0 49%
Immune Regulation of Tissue Repair-2.0-Rn v2.0 43%
Epithelial Innate Immune Activation-2.0-Rn v2.0 41%
Dendritic Cell Signaling-2.0-Rn v2.0 40%
Neutrophil Signaling-2.0-Rn v2.0 40%
Megakaryocyte Differentiation-2.0-Rn v2.0 37%
Epithelial Mucus Hypersecretion-2.0-Rn v2.0 36%
NK Signaling-2.0-Rn v2.0 33%
Macrophage Signaling-2.0-Hs v2.0 27%

Sample Edges

act(complex(SCOMP:"IkappaB Kinase Complex"), ma(kin)) directlyIncreases p(HGNC:NFKBIA, pmod(Ph, Ser, 36))

In the classical NF-{kappa}B signaling pathway, IKK{beta} is both necessary and sufficient for phosphorylation of I{kappa}B{alpha} on Ser 32 and Ser 36, and I{kappa}B{beta} on Ser 19 and Ser 23. PubMed:15371334

act(complex(SCOMP:"IkappaB Kinase Complex"), ma(kin)) directlyIncreases p(HGNC:NFKBIA, pmod(Ph, Ser, 36))

The IKK immunoprecipitates from thrombin-treated cells showed increased phosphorylation of GST-IkBalpha compared with the immunoprecipitates from control cells (Fig. 6), indicating the activation of IKK by thrombin. PubMed:15843586

act(complex(SCOMP:"IkappaB Kinase Complex"), ma(kin)) directlyIncreases p(HGNC:NFKBIA, pmod(Ph, Ser, 32))

In the classical NF-{kappa}B signaling pathway, IKK{beta} is both necessary and sufficient for phosphorylation of I{kappa}B{alpha} on Ser 32 and Ser 36, and I{kappa}B{beta} on Ser 19 and Ser 23. PubMed:15371334

Sample Nodes

p(RGD:Ppara)

In-Edges: 12 | Out-Edges: 20 | Explore Neighborhood | Download JSON

a(CHEBI:"nitric oxide")

In-Edges: 455 | Out-Edges: 538 | Classes: 3 | Explore Neighborhood | Download JSON

a(CHEBI:lipopolysaccharide)

In-Edges: 277 | Out-Edges: 1541 | Explore Neighborhood | Download JSON

a(CHEBI:"reactive oxygen species")

In-Edges: 1023 | Out-Edges: 827 | Classes: 1 | Children: 4 | Explore Neighborhood | Download JSON

p(RGD:Mapk3)

In-Edges: 173 | Out-Edges: 60 | 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.