ReviewFrontiers in genetics2020
Gene Regulatory Network Inference: Connecting Plant Biology and Mathematical Modeling.
Review in Frontiers in genetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 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
27 citing papers in PubMed.
- Problems With GO Enrichment as an Endpoint for Ecological Omics Interpretation.Molecular ecology · 2026Article
- Engineering principles in plant metabolism: integrating control, mechanics, and transport under dynamic environments.Plant physiology · 2026Review
- Conserved and divergent gene regulatory networks for crop drought resistance.Nature communications · 2026Article
- Insights into glandular trichome biology from analysis of organ-specific gene expression programmes in cannabis, hop and tomato.The Plant journal : for cell and molecular biology · 2026Article
- Big data approaches to understanding gene regulatory networks in the shoot apical meristem andFrontiers in plant science · 2026Review
- Metabolic Engineering of Terpenoid Biosynthesis in Medicinal Plants: From Genomic Insights to Biotechnological Applications.Current issues in molecular biology · 2025Review
- A space for time. Exploring temporal regulation of plant development across spatial scales.The Plant journal : for cell and molecular biology · 2025Review
- Accelerating crop improvement via integration of transcriptome-based network biology and genome editing.Planta · 2025Review
- Genomic and cell-specific regulation of benzylisoquinoline alkaloid biosynthesis in opium poppy.Journal of experimental botany · 2025Review
- Unraveling the multifaceted roles of SPL transcription factors in leaf development.Frontiers in plant science · 2025Review
- Machine Learning Inference of Gene Regulatory Networks in DevelopingPlants (Basel, Switzerland) · 2024Article
- Understanding developmental system drift.Development (Cambridge, England) · 2024Review
- Dynamic Intervention in Gene Regulatory Networks: A Partially Observed Zero-Sum Markov Game.Control Technology and Applications. Control Technology and Applications · 2024Article
- An optimal Bayesian intervention policy in response to unknown dynamic cell stimuli.Information sciences · 2024Article
- Recent advances in exploring transcriptional regulatory landscape of crops.Frontiers in plant science · 2024Review
- Article
- A multi-level approach reveals key physiological and molecular traits in the response of two rice genotypes subjected to water deficit at the reproductive stage.Plant-environment interactions (Hoboken, N.J.) · 2023Review
- Functional annotation of proteins for signaling network inference in non-model species.Nature communications · 2023Article
- Editorial: Cooperation of gene regulatory networks and phytohormones in cell development and morphogenesis.Frontiers in plant science · 2023Article
- Transcriptional signatures of wheat inflorescence development.Scientific reports · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Plant responses to environmental and intrinsic signals are tightly controlled by multiple transcription factors (TFs). These TFs and their regulatory connections form gene regulatory networks (GRNs), which provide a blueprint of the transcriptional regulations underlying plant development and environmental responses. This review provides examples of experimental methodologies commonly used to identify regulatory interactions and generate GRNs. Additionally, this review describes network inference techniques that leverage gene expression data to predict regulatory interactions. These computational and experimental methodologies yield complex networks that can identify new regulatory interactions, driving novel hypotheses. Biological properties that contribute to the complexity of GRNs are also described in this review. These include network topology, network size, transient binding of TFs to DNA, and competition between multiple upstream regulators. Finally, this review highlights the potential of machine learning approaches to leverage gene expression data to predict phenotypic outputs.
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.