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complex(GO:"TOR complex")

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Entity

Name
TOR complex
Namespace
go
Namespace Version
20180921
Namespace URL
https://raw.githubusercontent.com/pharmacome/terminology/b46b65c3da259b6e86026514dfececab7c22a11b/external/go-names.belns

Appears in Networks 2

Clearance of Amyloid Beta and Tau in Alzheimer’s Disease:from Mechanisms to Therapy v1.0.1

Alzheimer’s disease and the autophagic-lysosomal system v1.0.0

In-Edges 2

a(CHEBI:"amyloid-beta") positiveCorrelation act(complex(GO:"TOR complex")) View Subject | View Object

For instance, while accumulation of Aβ activates the mTOR signaling pathway and subsequently blocks macroautophagy, rapamycin reduces the Aβ load by enhancing macroautophagy [32] PubMed:29758300

Appears in Networks:

p(HGNC:TREM2) increases act(complex(GO:"TOR complex")) View Subject | View Object

TREM2 deficiency in an AD mouse model results in suppressed metabolic function in microglia through the dampening of the mTOR signaling pathway, which subsequently elicits a compensatory autophagic response to address the metabolic defect [109]. PubMed:29758300

Appears in Networks:
Annotations
Cell Ontology (CL)
microglial cell
MeSH
Alzheimer Disease

Out-Edges 2

complex(GO:"TOR complex") increases bp(GO:"lysosomal microautophagy") View Subject | View Object

And autophagy-lysosomal activity is induced via two signal pathways: mammalian target of rapamycin (mTOR)-dependent pathway and mTORindependent pathway (Tan et al. 2014b) PubMed:29626319

Appears in Networks:

act(complex(GO:"TOR complex")) positiveCorrelation a(CHEBI:"amyloid-beta") View Subject | View Object

For instance, while accumulation of Aβ activates the mTOR signaling pathway and subsequently blocks macroautophagy, rapamycin reduces the Aβ load by enhancing macroautophagy [32] PubMed:29758300

Appears in Networks:

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 PyBEL, an open source project. Please feel free to contact us here to give us feedback or report any issues. Also, see our Publishing Notes and Data Protection information.

If you find BEL Commons useful in your work, please consider citing: Hoyt, C. T., Domingo-Fernández, D., & Hofmann-Apitius, M. (2018). BEL Commons: an environment for exploration and analysis of networks encoded in Biological Expression Language. Database, 2018(3), 1–11.