ArticleBMC systems biology2016
Analysis of a dynamic model of guard cell signaling reveals the stability of signal propagation.
Article in BMC systems biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 15 citations in OpenAlex.
- Analysis of Electrome as a Tool for Plant Monitoring: Progress and Perspectives.Plants (Basel, Switzerland) · 2025Review
- Models of Cell Processes are Far from the Edge of Chaos.PRX life · 2023Article
- Inference of a Boolean Network From Causal Logic Implications.Frontiers in genetics · 2022Article
- A practical guide to mechanistic systems modeling in biology using a logic-based approach.Briefings in bioinformatics · 2021Review
- A Guard Cell Abscisic Acid (ABA) Network Model That Captures the Stomatal Resting State.Frontiers in physiology · 2020Article
- Therapeutic target discovery using Boolean network attractors: improvements of kali.Royal Society open science · 2018Article
- Identification of Biologically Essential Nodes via Determinative Power in Logical Models of Cellular Processes.Frontiers in physiology · 2018Article
- A new discrete dynamic model of ABA-induced stomatal closure predicts key feedback loops.PLoS biology · 2017Article
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAnalyzing the long-term behaviors (attractors) of dynamic models of biological systems can provide valuable insight into biological phenotypes and their stability. In this paper we identify the allowed long-term behaviors of a multi-level, 70-node dynamic model of the stomatal opening process in plants.
resultsWe start by reducing the model's huge state space. We first reduce unregulated nodes and simple mediator nodes, then simplify the regulatory functions of selected nodes while keeping the model consistent with experimental observations. We perform attractor analysis on the resulting 32-node reduced model by two methods: 1. converting it into a Boolean model, then applying two attractor-finding algorithms; 2. theoretical analysis of the regulatory functions. We further demonstrate the robustness of signal propagation by showing that a large percentage of single-node knockouts does not affect the stomatal opening level.
conclusionsCombining both methods with analysis of perturbation scenarios, we conclude that all nodes except two in the reduced model have a single attractor; and only two nodes can admit oscillations. The multistability or oscillations of these four nodes do not affect the stomatal opening level in any situation. This conclusion applies to the original model as well in all the biologically meaningful cases. In addition, the stomatal opening level is resilient against single-node knockouts. Thus, we conclude that the complex structure of this signal transduction network provides multiple information propagation pathways while not allowing extensive multistability or oscillations, resulting in robust signal propagation. Our innovative combination of methods offers a promising way to analyze multi-level models.
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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.