ReviewPlant physiology2013
Root systems biology: integrative modeling across scales, from gene regulatory networks to the rhizosphere.
Review in Plant physiology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 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
15 citing papers in PubMed.
- Cellular patterns in Arabidopsis root epidermis emerge from gene regulatory network and diffusion dynamical feedback.NPJ systems biology and applications · 2025Article
- Recent insights into metabolic and signalling events of directional root growth regulation and its implications for sustainable crop production systems.Frontiers in plant science · 2023Review
- Integrative Modelling of Gene Expression and Digital Phenotypes to Describe Senescence in Wheat.Genes · 2021Article
- Two decades of functional-structural plant modelling: now addressing fundamental questions in systems biology and predictive ecology.Annals of botany · 2020Review
- Three-Dimensional Time-Lapse Analysis Reveals Multiscale Relationships in Maize Root Systems with Contrasting Architectures.The Plant cell · 2019Article
- Review
- Genetic control of root growth: from genes to networks.Annals of botany · 2016Review
- Systems Biology for Smart Crops and Agricultural Innovation: Filling the Gaps between Genotype and Phenotype for Complex Traits Linked with Robust Agricultural Productivity and Sustainability.Omics : a journal of integrative biology · 2015Review
- Spatiotemporal modelling of hormonal crosstalk explains the level and patterning of hormones and gene expression in Arabidopsis thaliana wild-type and mutant roots.The New phytologist · 2015Article
- Re-analysis of RNA-seq transcriptome data reveals new aspects of gene activity in Arabidopsis root hairs.Frontiers in plant science · 2015Article
- The roots of future rice harvests.Rice (New York, N.Y.) · 2014Article
- Plant water uptake in drying soils.Plant physiology · 2014Review
- Linking metabolomics data to underlying metabolic regulation.Frontiers in molecular biosciences · 2014Review
- Transcriptional evidence for inferred pattern of pollen tube-stigma metabolic coupling during pollination.PloS one · 2014Article
- Hormonal crosstalk for root development: a combined experimental and modeling perspective.Frontiers in plant science · 2014Review
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
Abstract
Genetic and genomic approaches in model organisms have advanced our understanding of root biology over the last decade. Recently, however, systems biology and modeling have emerged as important approaches, as our understanding of root regulatory pathways has become more complex and interpreting pathway outputs has become less intuitive. To relate root genotype to phenotype, we must move beyond the examination of interactions at the genetic network scale and employ multiscale modeling approaches to predict emergent properties at the tissue, organ, organism, and rhizosphere scales. Understanding the underlying biological mechanisms and the complex interplay between systems at these different scales requires an integrative approach. Here, we describe examples of such approaches and discuss the merits of developing models to span multiple scales, from network to population levels, and to address dynamic interactions between plants and their environment.
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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.