Evidence map›Paper›PMID 26576197›Full record

ReviewComputational and mathematical methods in medicine2015

Time-Delayed Models of Gene Regulatory Networks.

K Parmar, K B Blyuss, Y N Kyrychko, S J Hogan

Abstract readReview
In one paragraph

Review in Computational and mathematical methods in medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Fokker-Planck representations of non-Markov Langevin equations: application to delayed systems.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2019
    Article
  6. Article
  7. Article
  8. Article
  9. 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.

K ParmarDepartment of Mathematics, University of Sussex, Falmer, Brighton BN1 9QH, UK.
K B BlyussDepartment of Mathematics, University of Sussex, Falmer, Brighton BN1 9QH, UK.
Y N KyrychkoDepartment of Mathematics, University of Sussex, Falmer, Brighton BN1 9QH, UK.
S J HoganDepartment of Engineering Mathematics, University of Bristol, Bristol BS8 1TR, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We discuss different mathematical models of gene regulatory networks as relevant to the onset and development of cancer. After discussion of alternative modelling approaches, we use a paradigmatic two-gene network to focus on the role played by time delays in the dynamics of gene regulatory networks. We contrast the dynamics of the reduced model arising in the limit of fast mRNA dynamics with that of the full model. The review concludes with the discussion of some open problems.

Indexed as

Gene Regulatory NetworksModels, GeneticComputational BiologyFuzzy LogicHumansMathematical ConceptsNeoplasmsNonlinear DynamicsRNA, MessengerRNA, NeoplasmStochastic ProcessesTime FactorsRNA, MessengerRNA, Neoplasm

Identifiers

PMID26576197
PMCPMC4632181

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.