Evidence map›Paper›PMID 28950873›Full record

ArticleBMC systems biology2017

Modeling and analysis of the Delta-Notch dependent boundary formation in the Drosophila large intestine.

Fei Liu, Deshun Sun, Ryutaro Murakami, Hiroshi Matsuno

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC systems biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Article
  2. Article
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

4 authors.

Fei LiuControl and Simulation Center, Harbin Institute of Technology, West Dazhi Street 92, Harbin, 150001, People's Republic of China. liufei@hit.edu.cn.
Deshun SunControl and Simulation Center, Harbin Institute of Technology, West Dazhi Street 92, Harbin, 150001, People's Republic of China.
Ryutaro MurakamiFaculty of Science, Yamaguchi University, Yoshida 1677-1, Yamaguchi, 753-8512, Japan.
Hiroshi MatsunoFaculty of Science, Yamaguchi University, Yoshida 1677-1, Yamaguchi, 753-8512, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe boundary formation in the Drosophila large intestine is widely studied as an important biological problem. It has been shown that the Delta-Notch signaling pathway plays an essential role in the formation of boundary cells.

resultsIn this paper, we propose a mathematical model for the Delta-Notch dependent boundary formation in the Drosophila large intestine in order to better interpret related experimental findings of this biological phenomenon. To achieve this, we not only perform stability analysis on the model from a theoretical point of view, but also perform numerical simulations to analyze the model with and without noises, the phenotype change with the change of Delta or Notch expression, and the perturbation influences of binding and inhibition parameters on the boundary formation.

conclusionsBy doing all these work, we can assure that our model can better interpret the biological findings related to the boundary formation in the Drosophila large intestine.

Indexed as

Models, BiologicalAnimalsDrosophila melanogasterDrosophila ProteinsGene Expression RegulationIntestine, LargeIntracellular Signaling Peptides and ProteinsMembrane ProteinsPhenotypeReceptors, NotchSignal Transductiondelta proteinDrosophila ProteinsIntracellular Signaling Peptides and ProteinsMembrane ProteinsN protein, DrosophilaReceptors, NotchBoundary formationDelta-Notch signaling pathwayDrosophila large intestineLocal stability analysisPerturbation analysisSimulation validation

Identifiers

PMID28950873
PMCPMC5615251

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.