Evidence map›Paper›PMID 19468305›Full record

ArticlePLoS computational biology2009

Computational models of the Notch network elucidate mechanisms of context-dependent signaling.

Smita Agrawal, Colin Archer, David V Schaffer

Open access · goldAbstract read
In one paragraph

Article in PLoS computational biology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed
3.1field-weighted citation impact, top 8% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

30 citing papers in PubMed, 72 citations in OpenAlex.

  1. Article
  2. Review
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  4. Article
  5. Notch pathway activation enhances cardiosphere in vitro expansion.Journal of cellular and molecular medicine · 2018
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  10. Dynamic properties of the segmentation clock mediated by microRNA.International journal of clinical and experimental pathology · 2015
    Article
  11. Article
  12. Article
  13. Stochastic simulation of notch signaling reveals novel factors that mediate the differentiation of neural stem cells.Journal of computational biology : a journal of computational molecular cell biology · 2014
    Article
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  15. Article
  16. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Smita AgrawalDepartment of Chemical Engineering, University of California Berkeley, Berkeley, California, United States of America.
Colin Archer
David V Schaffer
University of California, Berkeley · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Notch signaling pathway controls numerous cell fate decisions during development and adulthood through diverse mechanisms. Thus, whereas it functions as an oscillator during somitogenesis, it can mediate an all-or-none cell fate switch to influence pattern formation in various tissues during development. Furthermore, while in some contexts continuous Notch signaling is required, in others a transient Notch signal is sufficient to influence cell fate decisions. However, the signaling mechanisms that underlie these diverse behaviors in different cellular contexts have not been understood. Notch1 along with two downstream transcription factors hes1 and RBP-Jk forms an intricate network of positive and negative feedback loops, and we have implemented a systems biology approach to computationally study this gene regulation network. Our results indicate that the system exhibits bistability and is capable of switching states at a critical level of Notch signaling initiated by its ligand Delta in a particular range of parameter values. In this mode, transient activation of Delta is also capable of inducing prolonged high expression of Hes1, mimicking the "ON" state depending on the intensity and duration of the signal. Furthermore, this system is highly sensitive to certain model parameters and can transition from functioning as a bistable switch to an oscillator by tuning a single parameter value. This parameter, the transcriptional repression constant of hes1, can thus qualitatively govern the behavior of the signaling network. In addition, we find that the system is able to dampen and reduce the effects of biological noise that arise from stochastic effects in gene expression for systems that respond quickly to Notch signaling.This work thus helps our understanding of an important cell fate control system and begins to elucidate how this context dependent signaling system can be modulated in different cellular settings to exhibit entirely different behaviors.

Indexed as

Computational BiologyGene Regulatory NetworksModels, GeneticSignal TransductionTranscription, GeneticBasic Helix-Loop-Helix ProteinsComputer SimulationHomeodomain ProteinsImmunoglobulin J Recombination Signal Sequence-Binding ProteinPromoter Regions, GeneticReceptor, Notch1Repressor ProteinsStochastic ProcessesTranscription FactorsBasic Helix-Loop-Helix ProteinsHomeodomain ProteinsImmunoglobulin J Recombination Signal Sequence-Binding ProteinReceptor, Notch1Repressor ProteinsTranscription Factors

Identifiers

PMID19468305
PMCPMC2680760
OpenAlexW1970978593

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.