ArticleBiophysical journal2015
Spatiotemporal analysis of different mechanisms for interpreting morphogen gradients.
Article in Biophysical journal, 2015. 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.
- AI-powered simulation-based inference of a genuinely spatial-stochastic gene regulation model of early mouse embryogenesis.PLoS computational biology · 2024Article
- Single-cell directional sensing from just a few receptor binding events.Biophysical journal · 2023Article
- Short-time diffusive fluxes over membrane receptors yields the direction of a signalling source.Royal Society open science · 2023Article
- Implications of diffusion and time-varying morphogen gradients for the dynamic positioning and precision of bistable gene expression boundaries.PLoS computational biology · 2021Article
- Fold-change detection and scale invariance of cell-cell signaling in social amoeba.Proceedings of the National Academy of Sciences of the United States of America · 2017Article
- Dynamics robustness of cascading systems.PLoS computational biology · 2017Article
- Intrinsic Noise Profoundly Alters the Dynamics and Steady State of Morphogen-Controlled Bistable Genetic Switches.PLoS computational biology · 2016Article
- Morphogen rules: design principles of gradient-mediated embryo patterning.Development (Cambridge, England) · 2015Review
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Authors and funding
2 authors.
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Abstract
During development, multicellular organisms must accurately control both temporal and spatial aspects of tissue patterning. This is often achieved using morphogens, signaling molecules that form spatially varying concentrations and so encode positional information. Typical analysis of morphogens assumes that spatial information is decoded in steady state by measuring the value of the morphogen concentration. However, recent experimental work suggests that both pre-steady-state readout and measurement of spatial and temporal derivatives of the morphogen concentration can play important roles in defining boundaries. Here, we undertake a detailed theoretical and numerical study of the accuracy of patterning-both in space and time-in models where readout is provided not by the morphogen concentration but by its spatial and temporal derivatives. In both cases we find that accurate patterning can be achieved, with sometimes even smaller errors than directly reading the morphogen concentration. We further demonstrate that such models provide other potential benefits to the system, such as the ability to switch on and off gene response with a high degree of spatiotemporal accuracy. Finally, we discuss how such derivatives might be calculated biologically and examine these models in relation to Sonic Hedgehog signaling in the vertebrate central nervous system. We show that, when coupled to a downstream transcriptional network, pre-steady-state measurement of the temporal change in the Shh morphogen is a plausible mechanism for determining precise gene boundaries in both space and time.
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