ArticleGenome biology2013
Gene regulatory networks in plants: learning causality from time and perturbation.
Article in Genome biology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
38 citing papers in PubMed.
- Unlocking gene regulatory networks for crop resilience and sustainable agriculture.Nature biotechnology · 2025Review
- Model-to-crop conserved NUE Regulons enhance machine learning predictions of nitrogen use efficiency.The Plant cell · 2025Article
- Allelic variation in transcription factor PtoWRKY68 contributes to drought tolerance in Populus.Plant physiology · 2023Article
- A translatome-transcriptome multi-omics gene regulatory network reveals the complicated functional landscape of maize.Genome biology · 2023Article
- Article
- Gene Regulatory Network Modeling Using Single-Cell Multi-Omics in Plants.Methods in molecular biology (Clifton, N.J.) · 2023Article
- Article
- Photosynthetic Carbon Fixation and Sucrose Metabolism Supplemented by Weighted Gene Co-expression Network Analysis in Response to Water Stress in Rice With Overlapping Growth Stages.Frontiers in plant science · 2022Article
- Accurate determination of causalities in gene regulatory networks by dissecting downstream target genes.Frontiers in genetics · 2022Article
- Single-cell RNA sequencing of theeLife · 2021Article
- A forward genetics approach integrating genome-wide association study and expression quantitative trait locus mapping to dissect leaf development in maize (Zea mays).The Plant journal : for cell and molecular biology · 2021Article
- Nanotechnology and artificial intelligence to enable sustainable and precision agriculture.Nature plants · 2021Review
- Time-Based Systems Biology Approaches to Capture and Model Dynamic Gene Regulatory Networks.Annual review of plant biology · 2021Review
- CRISPR screens in plants: approaches, guidelines, and future prospects.The Plant cell · 2021Review
- Network Inference of Transcriptional Regulation in Germinating Low Phytic Acid Soybean Seeds.Frontiers in plant science · 2021Article
- Nitrate in 2020: Thirty Years from Transport to Signaling Networks.The Plant cell · 2020Review
- Nutrient dose-responsive transcriptome changes driven by Michaelis-Menten kinetics underlie plant growth rates.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
- Meta Gene Regulatory Networks in Maize Highlight Functionally Relevant Regulatory Interactions.The Plant cell · 2020Article
- Recent advances in gene function prediction using context-specific coexpression networks in plants.F1000Research · 2019Review
- Temporal transcriptional logic of dynamic regulatory networks underlying nitrogen signaling and use in plants.Proceedings of the National Academy of Sciences of the United States of America · 2018Article
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
The goal of systems biology is to generate models for predicting how a system will react under untested conditions or in response to genetic perturbations. This paper discusses experimental and analytical approaches to deriving causal relationships in gene regulatory networks.
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.