Evidence map›Paper›PMID 26279702›Full record

ArticleSystems and synthetic biology2015

Influence of parameter values on the oscillation sensitivities of two p53-Mdm2 models.

Christian E Cuba, Alexander R Valle, Giancarlo Ayala-Charca, Elizabeth R Villota, Alberto M Coronado

Abstract read
In one paragraph

Article in Systems and synthetic biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Christian E Cuba *Faculty of Mechanical Engineering, Universidad Nacional de Ingeniería, Av. Túpac Amaru s/n - Puerta 3, Pabellón A, Lima 25, Peru.
Alexander R Valle *Faculty of Mechanical Engineering, Universidad Nacional de Ingeniería, Av. Túpac Amaru s/n - Puerta 3, Pabellón A, Lima 25, Peru.
Giancarlo Ayala-CharcaFaculty of Mechanical Engineering, Universidad Nacional de Ingeniería, Av. Túpac Amaru s/n - Puerta 3, Pabellón A, Lima 25, Peru.
Elizabeth R VillotaFaculty of Mechanical Engineering, Universidad Nacional de Ingeniería, Av. Túpac Amaru s/n - Puerta 3, Pabellón A, Lima 25, Peru.
Alberto M CoronadoFaculty of Mechanical Engineering, Universidad Nacional de Ingeniería, Av. Túpac Amaru s/n - Puerta 3, Pabellón A, Lima 25, Peru.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Biomolecular networks that present oscillatory behavior are ubiquitous in nature. While some design principles for robust oscillations have been identified, it is not well understood how these oscillations are affected when the kinetic parameters are constantly changing or are not precisely known, as often occurs in cellular environments. Many models of diverse complexity level, for systems such as circadian rhythms, cell cycle or the p53 network, have been proposed. Here we assess the influence of hundreds of different parameter sets on the sensitivities of two configurations of a well-known oscillatory system, the p53 core network. We show that, for both models and all parameter sets, the parameter related to the p53 positive feedback, i.e. self-promotion, is the only one that presents sizeable sensitivities on extrema, periods and delay. Moreover, varying the parameter set values to change the dynamical characteristics of the response is more restricted in the simple model, whereas the complex model shows greater tunability. These results highlight the importance of the presence of specific network patterns, in addition to the role of parameter values, when we want to characterize oscillatory biochemical systems.

Indexed as

Global sensitivityOscillatory systemsP53 network

Identifiers

PMID26279702
PMCPMC4531880

What OpenQuestion holds

Textmetadata
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.