Evidence map›Paper›PMID 41759532›Full record

ArticleCell systems2026

Genetic resonance in the p53 signaling network.

Mathias S Heltberg, Alba Jimenez, Galit Lahav, Mogens H Jensen

Abstract read
In one paragraph

Article in Cell systems, 2026. 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

4 authors.

Mathias S HeltbergNiels Bohr Institute, University of Copenhagen, 2100 Copenhagen, Denmark.
Alba JimenezDepartment of Systems Biology, Blavatnik Institute at Harvard Medical School, Boston, MA, USA.
Galit LahavDepartment of Systems Biology, Blavatnik Institute at Harvard Medical School, Boston, MA, USA. Electronic address: galit@hms.harvard.edu.
Mogens H JensenNiels Bohr Institute, University of Copenhagen, 2100 Copenhagen, Denmark. Electronic address: mhjensen@nbi.dk.

Funding

Dynamics, Regulation and Function of p53 in Single CellsR35GM139572 · NIGMS · HARVARD MEDICAL SCHOOL · PI Galit Lahav · 2021 to 2026
$4.7M
NIGMS NIH HHS R35 GM139572
6 · The paper itself

Abstract

Resonance allows systems to amplify their response to periodic stimuli and is well established in physics but not yet described in gene regulatory networks. Here, we asked whether resonance exists in the dynamics of p53, a tumor suppressor that oscillates after DNA damage to activate growth-inhibitory pathways. We developed a mathematical framework predicting that p53 exhibits damped oscillations after a single stimulus and frequency-dependent amplitudes under periodic stimulation, both hallmarks of resonance. Using live single-cell imaging, we confirmed these predictions: a single drug pulse that stabilizes p53 produced damped oscillations, while periodic pulses triggered frequency-dependent responses with maximal amplitudes at the natural p53 oscillation frequency as well as minor peaks. Finally, theoretical analysis suggested that resonance may enhance transcriptional responses and selectively activate downstream targets. Together, our results identify resonance as a regulatory principle in gene networks, potentially linking oscillations of transcription factors with selective gene activation through signal amplification.

Indexed as

Gene Regulatory NetworksSignal TransductionTumor Suppressor Protein p53DNA DamageHumansTranscription FactorsTranscription FactorsTumor Suppressor Protein p53cellular regulationdamped oscillationsenhanced transcriptiongenetic oscillationsnon-linear resonancep53 networkresonanceselective gene expressionsignal amplification

Identifiers

PMID41759532
PMCPMC13401894

What OpenQuestion holds

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Registered trials

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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.