ReviewFrontiers in plant science2025
Biophysical modelling as a tool for advancing plant science and engineering.
Review in Frontiers in plant science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- From Prediction to Creation: Generative Plant Design.Plants (Basel, Switzerland) · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Plant growth, development, and physiology are governed by complex processes operating across scales spanning from molecular, cellular, tissue, and whole organism. Experimental studies have uncovered key mechanisms underlying hormone signalling, gene regulation, metabolism, and environmental responses. However, integrating this information into a unified framework to understand the mechanistic origin, evolution, and robustness of plant form and function remains challenging. Mathematical and computational modelling provides powerful tools to address this challenge, where simulation and predictions offer strategic guidance for efficient experimental search of missing information underlying plant processes. In this review, we discuss a broad spectrum of modelling approaches, including reaction-kinetic and Boolean network models for molecular and genetic regulation; mechanical and geometry-based models for tissue growth and morphogenesis; metabolic and constraint-based models for resource allocation; and hydraulic and electrophysiological models for physiological transport processes. We also propose that by combining different modelling strategies, researchers can develop predictive tools for biotechnological applications, including enhancement of stress tolerance, efficient use of nutrients, regenerative tissue engineering, and biomass productivity.
Indexed as
Identifiers
What Socratic 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 Socratic graph.