Evidence map›Paper›PMID 23283238›Full record

ArticleBiophysical journal2012

Crosstalk and competition in signaling networks.

Michael A Rowland, Walter Fontana, Eric J Deeds

Open access · bronzeAbstract read
In one paragraph

Article in Biophysical journal, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed
3.1field-weighted citation impact, top 8% of its field
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

34 citing papers in PubMed, 63 citations in OpenAlex.

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  9. A new precision medicine initiative at the dawn of exascale computing.Signal transduction and targeted therapy · 2021
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  19. Fundamental trade-offs between information flow in single cells and cellular populations.Proceedings of the National Academy of Sciences of the United States of America · 2017
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 1 country.

Michael A RowlandCenter for Bioinformatics, University of Kansas, Lawrence, KS, USA.
Walter Fontana
Eric J Deeds
University of Kansas · USCenter for Systems Biology · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Signaling networks have evolved to transduce external and internal information into critical cellular decisions such as growth, differentiation, and apoptosis. These networks form highly interconnected systems within cells due to network crosstalk, where an enzyme from one canonical pathway acts on targets from other pathways. It is currently unclear what types of effects these interconnections can have on the response of networks to incoming signals. In this work, we employ mathematical models to characterize the influence that multiple substrates have on one another. These models build off of the atomistic motif of a kinase/phosphatase pair acting on a single substrate. We find that the ultrasensitive, switch-like response these motifs can exhibit becomes transitive: if one substrate saturates the enzymes and responds ultrasensitively, then all substrates will do so regardless of their degree of saturation. We also demonstrate that the phosphatases themselves can induce crosstalk even when the kinases are independent. These findings have strong implications for how we understand and classify crosstalk, as well as for the rational development of kinase inhibitors aimed at pharmaceutically modulating network behavior.

Indexed as

Models, BiologicalAnimalsCell CommunicationComputer SimulationHumansMultienzyme ComplexesSignal TransductionMultienzyme Complexes

Identifiers

PMID23283238
PMCPMC3514525
OpenAlexW2053733974

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.