ArticlePLoS computational biology2015
Automated Identification of Core Regulatory Genes in Human Gene Regulatory Networks.
Article in PLoS computational biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 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
20 citing papers in PubMed.
- Transcriptional regulatory network analysis uncovers modular gene control and potential key regulators in diabetic cardiomyopathy.Frontiers in cell and developmental biology · 2026Article
- Drug Discovery from Gene Expression/Gene Regulation.Methods in molecular biology (Clifton, N.J.) · 2026Review
- Aggregation of recount3 RNA-seq data improves inference of consensus and tissue-specific gene coexpression networks.Genome research · 2025Article
- Identifying Key Regulators of Keratinization in Lung Squamous Cell Cancer Using Integrated TCGA Analysis.Cancers · 2023Article
- Analyzing integrated network of methylation and gene expression profiles in lung squamous cell carcinoma.Scientific reports · 2022Article
- Revelation of candidate genes and molecular mechanism of reproductive seasonality in female rohu (Labeo rohita Ham.) by RNA sequencing.BMC genomics · 2021Article
- Article
- Exploring the Molecular Mechanism of Liuwei Dihuang Pills for Treating Diabetic Nephropathy by Combined Network Pharmacology and Molecular Docking.Evidence-based complementary and alternative medicine : eCAM · 2021Article
- Identification of robust genes in transcriptional regulatory network of Mycobacterium tuberculosis.IET systems biology · 2020Article
- Competing endogenous RNA crosstalk at system level.PLoS computational biology · 2019Article
- Regulation of Early Host Immune Responses Shapes the Pathogenicity of Avian Influenza A Virus.Frontiers in microbiology · 2019Article
- The Role of EGFR in Influenza Pathogenicity: Multiple Network-Based Approaches to Identify a Key Regulator of Non-lethal Infections.Frontiers in cell and developmental biology · 2019Article
- Hierarchical closeness-based properties reveal cancer survivability and biomarker genes in molecular signaling networks.PloS one · 2018Article
- Graph complexity analysis identifies an ETV5 tumor-specific network in human and murine low-grade glioma.PloS one · 2018Article
- Article
- Exploring conserved mRNA-miRNA interactions in colon and lung cancers.Gastroenterology and hepatology from bed to bench · 2017Article
- Celiac disease and hepatitis C relationships in transcriptional regulatory networks.Gastroenterology and hepatology from bed to bench · 2017Article
- Gene expression patterns in transgenic mouse models of hypertrophic cardiomyopathy caused by mutations in myosin regulatory light chain.Archives of biochemistry and biophysics · 2016Article
- The hnRNP-Htt axis regulates necrotic cell death induced by transcriptional repression through impaired RNA splicing.Cell death & disease · 2016Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Human gene regulatory networks (GRN) can be difficult to interpret due to a tangle of edges interconnecting thousands of genes. We constructed a general human GRN from extensive transcription factor and microRNA target data obtained from public databases. In a subnetwork of this GRN that is active during estrogen stimulation of MCF-7 breast cancer cells, we benchmarked automated algorithms for identifying core regulatory genes (transcription factors and microRNAs). Among these algorithms, we identified K-core decomposition, pagerank and betweenness centrality algorithms as the most effective for discovering core regulatory genes in the network evaluated based on previously known roles of these genes in MCF-7 biology as well as in their ability to explain the up or down expression status of up to 70% of the remaining genes. Finally, we validated the use of K-core algorithm for organizing the GRN in an easier to interpret layered hierarchy where more influential regulatory genes percolate towards the inner layers. The integrated human gene and miRNA network and software used in this study are provided as supplementary materials (S1 Data) accompanying this manuscript.
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.