ArticleEpigenetics2021
A mathematical model exhibiting the effect of DNA methylation on the stability boundary in cell-fate networks.
Article in Epigenetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
8 citing papers in PubMed.
- Stochastic modeling of epigenetic memory.NPJ systems biology and applications · 2026Review
- Article
- Order-of-Mutation Effects on Cancer Progression: Models for Myeloproliferative Neoplasm.Bulletin of mathematical biology · 2024Article
- Epigenetic OCT4 regulatory network: stochastic analysis of cellular reprogramming.NPJ systems biology and applications · 2024Article
- Epigenetic memory acquired during long-term EMT induction governs the recovery to the epithelial state.Journal of the Royal Society, Interface · 2023Article
- Epigenetic factor competition reshapes the EMT landscape.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- Epigenetic cell memory: The gene's inner chromatin modification circuit.PLoS computational biology · 2022Article
- Modeling aging and its impact on cellular function and organismal behavior.Experimental gerontology · 2021Review
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.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cell-fate networks are traditionally studied within the framework of gene regulatory networks. This paradigm considers only interactions of genes through expressed transcription factors and does not incorporate chromatin modification processes. This paper introduces a mathematical model that seamlessly combines gene regulatory networks and DNA methylation (DNAm), with the goal of quantitatively characterizing the contribution of epigenetic regulation to gene silencing. The 'Basin of Attraction percentage' is introduced as a metric to quantify gene silencing abilities. As a case study, a computational and theoretical analysis is carried out for a model of the pluripotent stem cell circuit as well as a simplified self-activating gene model. The results confirm that the methodology quantitatively captures the key role that DNAm plays in enhancing the stability of the silenced gene state.
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.