ArticlePLoS computational biology2014
Construction and validation of a regulatory network for pluripotency and self-renewal of mouse embryonic stem cells.
Article in PLoS computational biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers.
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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.
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Who cites it
53 citing papers in PubMed, 107 citations in OpenAlex.
- Transcriptional Bursting in Pluripotent Stem Cells.Biology · 2026Review
- Unveiling gene perturbation effects through gene regulatory networks inference from single-cell transcriptomic data.PLoS computational biology · 2026Article
- LogicSR: prior-guided symbolic regression for gene regulatory network inference from single-cell transcriptomics data.Briefings in bioinformatics · 2025Article
- p53-inducible lncRNA LOC644656 causes genotoxic stress-induced stem cell maldifferentiation and cancer chemoresistance.Nature communications · 2025Article
- The regulatory architecture of the primed pluripotent cell state.Nature communications · 2025Article
- Unravelling Convergent Signaling Mechanisms Underlying the Aging-Disease Nexus Using Computational Language Analysis.Current issues in molecular biology · 2025Article
- TopoDoE: a design of experiment strategy for selection and refinement in ensembles of executable gene regulatory networks.BMC bioinformatics · 2024Article
- Mechanisms of Embryonic Stem Cell Pluripotency Maintenance and Their Application in Livestock and Poultry Breeding.Animals : an open access journal from MDPI · 2024Review
- Approaches for Benchmarking Single-Cell Gene Regulatory Network Methods.Bioinformatics and biology insights · 2024Review
- Comparative developmental genomics of sex-biased gene expression in early embryogenesis across mammals.Biology of sex differences · 2023Article
- Depicting pseudotime-lagged causality across single-cell trajectories for accurate gene-regulatory inference.PNAS nexus · 2023Article
- Identifying strengths and weaknesses of methods for computational network inference from single-cell RNA-seq data.G3 (Bethesda, Md.) · 2023Article
- CELLoGeNe - An energy landscape framework for logical networks controlling cell decisions.iScience · 2022Article
- Bayesian information sharing enhances detection of regulatory associations in rare cell types.Bioinformatics (Oxford, England) · 2021Article
- A Systematic Analysis Identifies Key Regulators Involved in Cell Proliferation and Potential Drugs for the Treatment of Human Lung Adenocarcinoma.Frontiers in oncology · 2021Article
- A mathematical modelling framework for the regulation of intra-cellular OCT4 in human pluripotent stem cells.PloS one · 2021Article
- TINC- A Method to Dissect Regulatory Complexes at Single-Locus Resolution- Reveals an Extensive Protein Complex at the Nanog Promoter.Stem cell reports · 2020Article
- Reconstructing gene regulatory networks in single-cell transcriptomic data analysis.Zoological research · 2020Review
- Integrative and perturbation-based analysis of the transcriptional dynamics of TGFβ/BMP system components in transition from embryonic stem cells to neural progenitors.Stem cells (Dayton, Ohio) · 2020Article
- netNMF-sc: leveraging gene-gene interactions for imputation and dimensionality reduction in single-cell expression analysis.Genome research · 2020Article
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
A 30-node signed and directed network responsible for self-renewal and pluripotency of mouse embryonic stem cells (mESCs) was extracted from several ChIP-Seq and knockdown followed by expression prior studies. The underlying regulatory logic among network components was then learned using the initial network topology and single cell gene expression measurements from mESCs cultured in serum/LIF or serum-free 2i/LIF conditions. Comparing the learned network regulatory logic derived from cells cultured in serum/LIF vs. 2i/LIF revealed differential roles for Nanog, Oct4/Pou5f1, Sox2, Esrrb and Tcf3. Overall, gene expression in the serum/LIF condition was more variable than in the 2i/LIF but mostly consistent across the two conditions. Expression levels for most genes in single cells were bimodal across the entire population and this motivated a Boolean modeling approach. In silico predictions derived from removal of nodes from the Boolean dynamical model were validated with experimental single and combinatorial RNA interference (RNAi) knockdowns of selected network components. Quantitative post-RNAi expression level measurements of remaining network components showed good agreement with the in silico predictions. Computational removal of nodes from the Boolean network model was also used to predict lineage specification outcomes. In summary, data integration, modeling, and targeted experiments were used to improve our understanding of the regulatory topology that controls mESC fate decisions as well as to develop robust directed lineage specification protocols.
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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.