ArticleBiophysical journal2017
Translating ceRNA Susceptibilities into Correlation Functions.
Article in Biophysical journal, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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.
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.
Who cites it
4 citing papers in PubMed, 7 citations in OpenAlex.
- Out-of-Equilibrium ceRNA Crosstalk.Methods in molecular biology (Clifton, N.J.) · 2025Article
- Competing endogenous RNA crosstalk at system level.PLoS computational biology · 2019Article
- Stochastic sequestration dynamics: a minimal model with extrinsic noise for bimodal distributions and competitors correlation.Scientific reports · 2018Article
- Molecular Network-Based Identification of Competing Endogenous RNAs in Thyroid Carcinoma.Genes · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Competition to bind microRNAs induces an effective positive cross talk between their targets, which are therefore known as "competing endogenous RNAs" (ceRNAs). Although such an effect is known to play a significant role in specific situations, estimating its strength from data and experimentally in physiological conditions appears to be far from simple. Here, we show that the susceptibility of ceRNAs to different types of perturbations affecting their competitors (and hence their tendency to cross talk) can be encoded in quantities as intuitive and as simple to measure as correlation functions. This scenario is confirmed by extensive numerical simulations and validated by re-analyzing phosphatase and tensin homolog's cross-talk pattern from The Cancer Genome Atlas breast cancer database. These results clarify the links between different quantities used to estimate the intensity of ceRNA cross talk and provide, to our knowledge, new keys to analyze transcriptional data sets and effectively probe ceRNA networks in silico.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.