Evidence map›Paper›PMID 23383305›Full record

ArticlePloS one2013

Protein complex formation: computational clarification of the sequential versus probabilistic recruitment puzzle.

Manuel Schölling, Stefan Thurner, Rudolf Hanel

Abstract read
In one paragraph

Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

3 authors.

Manuel SchöllingSection for Science of Complex Systems/CeMSIIS, Medical University of Vienna, Vienna, Austria.
Stefan Thurner
Rudolf Hanel

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Our current view on how protein complexes assemble and disassemble at promoter sites is based on experimental data. For instance this data is provided by biochemical methods (e.g. ChIP-on-chip assays) or GFP-based assays. These two approaches suggest very different characteristics for protein recruitment processes that regulate and initiate gene transcription. Biochemical methods suggest a strictly ordered and consecutive protein recruitment while GFP-based assays draw a picture much closer to chaotic or stochastic recruitment. To understand the reason for these conflicting results, we design a generalized recruitment model (GRM) that allows to simulate all possible scenarios between strictly sequential recruitment and completely probabilistic recruitment. With this model we show that probabilistic, transient binding events that are visible in GFP experiments can not be detected by ChIP experiments. We demonstrate that sequential recruitment processes and probabilistic recruitment processes that contain "shortcuts" exhibit periodic dynamics and are hard to distinguish with standard ChIP measurements. Therefore we propose a simple experimental method that can be used to discriminate sequential from probabilistic recruitment processes. We discuss the limitations of this method.

Indexed as

Models, BiologicalChromatin ImmunoprecipitationComputational BiologyGreen Fluorescent ProteinsMultiprotein ComplexesProbabilityPromoter Regions, GeneticProteinsGreen Fluorescent ProteinsMultiprotein ComplexesProteins

Identifiers

PMID23383305
PMCPMC3562237

What OpenQuestion holds

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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.