Evidence map›Paper›PMID 39702709›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2025

Out-of-Equilibrium ceRNA Crosstalk.

Elsi Ferro, Candela L Szischik, Marta Cunial, Alejandra C Ventura, Andrea De Martino, Carla Bosia

Abstract read
PubMed Publisher
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

6 authors.

Elsi FerroDepartment of Applied Science and Technology, Politecnico di Torino, Corso Duca degli Abruzzi, Torino, Italy.
Candela L SzischikUniversidad de Buenos Aires, Facultad de Ciencias Exactas y Naturales, Departamento de Física, Ciudad Universitaria, Buenos Aires, Argentina.
Marta CunialItalian Institute for Genomic Medicine, c/o IRCCS, Str. Prov. le, Candiolo, Italy.
Alejandra C VenturaUniversidad de Buenos Aires, Facultad de Ciencias Exactas y Naturales, Departamento de Física, Ciudad Universitaria, Buenos Aires, Argentina.
Andrea De MartinoDepartment of Applied Science and Technology, Politecnico di Torino, Corso Duca degli Abruzzi, Torino, Italy.
Carla BosiaDepartment of Applied Science and Technology, Politecnico di Torino, Corso Duca degli Abruzzi, Torino, Italy. carla.bosia@polito.it.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Among non-coding RNAs, microRNAs are pivotal post-transcriptional regulators of gene expression in higher eukaryotes. Through a titration-based mechanism of interaction with their target RNAs, microRNAs can mediate a weak but pervasive form of RNA cross-regulation, as different endogenous RNAs can be effectively coupled by competing for microRNA binding (a phenomenon now known as "crosstalk"). Mathematical modeling has been proven of great help in unraveling many features of these competing endogenous RNA (ceRNA) interactions. However, although many studies have been devoted to the steady-state properties of this indirect regulatory layer, little is known about how the information encoded in frequency, amplitude, duration, and other features of regulatory signals can affect the resulting ceRNA crosstalk picture and hence the overall patterns of gene expression. Here, we focus on such dynamical aspects, with a special emphasis on the encoding and decoding of time-dependent signals.

Indexed as

Gene Expression RegulationMicroRNAsGene Regulatory NetworksHumansModels, GeneticRNA, Competitive EndogenousRNA, MessengerMicroRNAsRNA, Competitive EndogenousRNA, MessengerceRNACrosstalkFrequency preferencemiRNAOut-of-equilibrium

Identifiers

PMID39702709

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.