Regulatory phosphorylation of eIF6 by GSK3
Ontology highlight
ABSTRACT:
INSTRUMENT(S): LTQ Orbitrap Elite
ORGANISM(S): Homo Sapiens (ncbitaxon:9606)
SUBMITTER: 
Dr. Sofia Origanti
PROVIDER: MSV000085596 | MassIVE | Tue Jun 16 12:41:00 BST 2020
SECONDARY ACCESSION(S): PXD019818
REPOSITORIES: MassIVE
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Project description:Chavez2009 - a core regulatory network of OCT4 in human embryonic stem cells
A core OCT4-regulated network has been identified as a test case, to analyase stem cell characteristics and cellular differentiation.
This model is described in the article:
In silico identification of a core regulatory network of OCT4 in human embryonic stem cells using an integrated approach.
Chavez L, Bais AS, Vingron M, Lehrach H, Adjaye J, Herwig R
BMC Genomics, 2009, 10:314
Abstract:
BACKGROUND: The transcription factor OCT4 is highly expressed in pluripotent embryonic stem cells which are derived from the inner cell mass of mammalian blastocysts. Pluripotency and self renewal are controlled by a transcription regulatory network governed by the transcription factors OCT4, SOX2 and NANOG. Recent studies on reprogramming somatic cells to induced pluripotent stem cells highlight OCT4 as a key regulator of pluripotency.
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CONCLUSION: Our analysis shows how heterogeneous functional information can be integrated in order to reconstruct gene regulatory networks. As a test case we identified a core OCT4-regulated network that is important for the analysis of stem cell characteristics and cellular differentiation. Functional information is largely enriched using different experimental results. The de novo motif discovery identified well-known regulators closely connected to the OCT4 network as well as potential new regulators of pluripotency and differentiation. These results provide the basis for further targeted functional studies.
This model is hosted on BioModels Database
and identified
by: MODEL1305010000
.
To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource
for published quantitative kinetic models
.
To the extent possible under law, all copyright and related or
neighbouring rights to this encoded model have been dedicated to the public
domain worldwide. Please refer to CC0 Public Domain
Dedication
for more information.
2005-01-01 | MODEL1305010000 | BioModels
Project description:Mukhopadhyay2013 - T cell receptor proximal
signaling reveals emergent ultrasensitivity
This model is described in the article:
Systems model of T cell
receptor proximal signaling reveals emergent
ultrasensitivity.
Mukhopadhyay H, Cordoba SP, Maini
PK, van der Merwe PA, Dushek O.
PLoS Comput. Biol. 2013; 9(3):
e1003004
Abstract:
Receptor phosphorylation is thought to be tightly regulated
because phosphorylated receptors initiate signaling cascades
leading to cellular activation. The T cell antigen receptor
(TCR) on the surface of T cells is phosphorylated by the kinase
Lck and dephosphorylated by the phosphatase CD45 on multiple
immunoreceptor tyrosine-based activation motifs (ITAMs).
Intriguingly, Lck sequentially phosphorylates ITAMs and ZAP-70,
a cytosolic kinase, binds to phosphorylated ITAMs with
differential affinities. The purpose of multiple ITAMs, their
sequential phosphorylation, and the differential ZAP-70
affinities are unknown. Here, we use a systems model to show
that this signaling architecture produces emergent
ultrasensitivity resulting in switch-like responses at the
scale of individual TCRs. Importantly, this switch-like
response is an emergent property, so that removal of multiple
ITAMs, sequential phosphorylation, or differential affinities
abolishes the switch. We propose that highly regulated TCR
phosphorylation is achieved by an emergent switch-like response
and use the systems model to design novel chimeric antigen
receptors for therapy.
This model is hosted on
BioModels Database
and identified by:
MODEL1604100000.
To cite BioModels Database, please use:
BioModels Database:
An enhanced, curated and annotated resource for published
quantitative kinetic models.
To the extent possible under law, all copyright and related or
neighbouring rights to this encoded model have been dedicated to
the public domain worldwide. Please refer to
CC0
Public Domain Dedication for more information.
2016-11-03 | MODEL1604100000 | BioModels