Evidence map›Paper›PMID 18445552›Full record

ArticleJournal of the Royal Society, Interface2008

Adaptive dynamics with a single two-state protein.

Attila Csikász-Nagy, Orkun S Soyer

Abstract read
In one paragraph

Article in Journal of the Royal Society, Interface, 2008. 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. Article
  3. Review
  4. Article
  5. Article
  6. Adaptive response by state-dependent inactivation.Proceedings of the National Academy of Sciences of the United States of America · 2009
    Article
  7. Article
  8. Article
  9. Biological switches and clocks.Journal of the Royal Society, Interface · 2008
    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

2 authors.

Attila Csikász-NagyMicrosoft Research-University of Trento Centre for Computational and Systems Biology, Piazza Manci 17, Povo (Trento), Italy. csikasz@cosbi.eu
Orkun S Soyer

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

An important step towards understanding biological systems is to relate simple biochemical elements to dynamics. Here, we present the arguably simplest dynamical element in biochemical networks. It consists of a single protein with two states (active and inactive) and an external signal that catalyses the conversion between these two states. Further, there is steady synthesis and degradation of the inactive and active forms, respectively. As this element captures both structural and dynamical features of biochemical networks at the lowest level, we refer to it as a biochemical network unit (BioNetUnit). Using both simulations and mathematical analysis, we find that BioNetUnit shows perfect adaptation that leads to temporal responses to step changes in the incoming signal. Compared with a well-described adaptive system, which is found in bacterial chemotaxis, BioNetUnit has lower sensitivity and its adaptation time is less robust to the base signal levels. We show that these dynamical limitations lead to 'once-and-only-once' responses for certain signal sequences. These findings demonstrate that BioNetUnit is relevant in adaptive and cyclic processes. In particular, it could be seen as a generic representation for ligand-activated receptors that are desensitized upon continuous activation. The analysis of coupled BioNetUnits will show how the presented dynamics at single unit will change upon increased system complexity and how such systems would mediate biological functions.

Indexed as

Models, BiologicalAdaptation, PhysiologicalBacterial Physiological PhenomenaChemotaxisLigandsProteinsReceptors, Cell SurfaceSignal TransductionLigandsProteinsReceptors, Cell Surface

Identifiers

PMID18445552
PMCPMC2706455

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.