ArticleFrontiers in genetics2021
Filtering of Data-Driven Gene Regulatory Networks Using
Article in Frontiers in genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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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.
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.
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Who cites it
7 citing papers in PubMed, 7 citations in OpenAlex.
- GRNContext: an interactive web platform for contextualized gene regulatory networks visualization across human cancers.Bioinformatics (Oxford, England) · 2026Article
- Integrated Gene Regulatory Network Analysis Reveals Coordinated Transcriptional Reprogramming in thePlants (Basel, Switzerland) · 2026Article
- The Vitamin D Receptor Ortholog Hr96 Modulates Neuronal and Mitochondrial Dynamics in a Drosophila Model of Alzheimer's Disease.Molecular neurobiology · 2025Article
- Organ-level gene-regulatory networks inferred from transcriptomic data reveal context-specific regulation and highlight novel regulators of ripening and ABA-mediated responses in tomato.Plant communications · 2025Article
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- A comprehensive transcription factor and DNA-binding motif resource for the construction of gene regulatory networks inComputational and structural biotechnology journal · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Gene Regulatory Networks (GRNs) allow the study of regulation of gene expression of whole genomes. Among the most relevant advantages of using networks to depict this key process, there is the visual representation of large amounts of information and the application of graph theory to generate new knowledge. Nonetheless, despite the many uses of GRNs, it is still difficult and expensive to assign Transcription Factors (TFs) to the regulation of specific genes. ChIP-Seq allows the determination of TF Binding Sites (TFBSs) over whole genomes, but it is still an expensive technique that can only be applied one TF at a time and requires replicates to reduce its noise. Once TFBSs are determined, the assignment of each TF and its binding sites to the regulation of specific genes is not trivial, and it is often performed by carrying out site-specific experiments that are unfeasible to perform in all possible binding sites. Here, we addressed these relevant issues with a two-step methodology using
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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.