Automated numerical simulation of biological pattern formation based on visual feedback simulation framework.

There are various fantastic biological phenomena in biological pattern formation. Mathematical modeling using reaction-diffusion partial differential equation systems is employed to study the mechanism of pattern formation. However, model parameter selection is both difficult and time consuming. In...

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Main Authors: Mingzhu Sun, Hui Xu, Xingjuan Zeng, Xin Zhao
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2017-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC5321435?pdf=render
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spelling doaj-7f37e04da54a4515913b188384c5c3b82020-11-24T21:52:39ZengPublic Library of Science (PLoS)PLoS ONE1932-62032017-01-01122e017264310.1371/journal.pone.0172643Automated numerical simulation of biological pattern formation based on visual feedback simulation framework.Mingzhu SunHui XuXingjuan ZengXin ZhaoThere are various fantastic biological phenomena in biological pattern formation. Mathematical modeling using reaction-diffusion partial differential equation systems is employed to study the mechanism of pattern formation. However, model parameter selection is both difficult and time consuming. In this paper, a visual feedback simulation framework is proposed to calculate the parameters of a mathematical model automatically based on the basic principle of feedback control. In the simulation framework, the simulation results are visualized, and the image features are extracted as the system feedback. Then, the unknown model parameters are obtained by comparing the image features of the simulation image and the target biological pattern. Considering two typical applications, the visual feedback simulation framework is applied to fulfill pattern formation simulations for vascular mesenchymal cells and lung development. In the simulation framework, the spot, stripe, labyrinthine patterns of vascular mesenchymal cells, the normal branching pattern and the branching pattern lacking side branching for lung branching are obtained in a finite number of iterations. The simulation results indicate that it is easy to achieve the simulation targets, especially when the simulation patterns are sensitive to the model parameters. Moreover, this simulation framework can expand to other types of biological pattern formation.http://europepmc.org/articles/PMC5321435?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Mingzhu Sun
Hui Xu
Xingjuan Zeng
Xin Zhao
spellingShingle Mingzhu Sun
Hui Xu
Xingjuan Zeng
Xin Zhao
Automated numerical simulation of biological pattern formation based on visual feedback simulation framework.
PLoS ONE
author_facet Mingzhu Sun
Hui Xu
Xingjuan Zeng
Xin Zhao
author_sort Mingzhu Sun
title Automated numerical simulation of biological pattern formation based on visual feedback simulation framework.
title_short Automated numerical simulation of biological pattern formation based on visual feedback simulation framework.
title_full Automated numerical simulation of biological pattern formation based on visual feedback simulation framework.
title_fullStr Automated numerical simulation of biological pattern formation based on visual feedback simulation framework.
title_full_unstemmed Automated numerical simulation of biological pattern formation based on visual feedback simulation framework.
title_sort automated numerical simulation of biological pattern formation based on visual feedback simulation framework.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2017-01-01
description There are various fantastic biological phenomena in biological pattern formation. Mathematical modeling using reaction-diffusion partial differential equation systems is employed to study the mechanism of pattern formation. However, model parameter selection is both difficult and time consuming. In this paper, a visual feedback simulation framework is proposed to calculate the parameters of a mathematical model automatically based on the basic principle of feedback control. In the simulation framework, the simulation results are visualized, and the image features are extracted as the system feedback. Then, the unknown model parameters are obtained by comparing the image features of the simulation image and the target biological pattern. Considering two typical applications, the visual feedback simulation framework is applied to fulfill pattern formation simulations for vascular mesenchymal cells and lung development. In the simulation framework, the spot, stripe, labyrinthine patterns of vascular mesenchymal cells, the normal branching pattern and the branching pattern lacking side branching for lung branching are obtained in a finite number of iterations. The simulation results indicate that it is easy to achieve the simulation targets, especially when the simulation patterns are sensitive to the model parameters. Moreover, this simulation framework can expand to other types of biological pattern formation.
url http://europepmc.org/articles/PMC5321435?pdf=render
work_keys_str_mv AT mingzhusun automatednumericalsimulationofbiologicalpatternformationbasedonvisualfeedbacksimulationframework
AT huixu automatednumericalsimulationofbiologicalpatternformationbasedonvisualfeedbacksimulationframework
AT xingjuanzeng automatednumericalsimulationofbiologicalpatternformationbasedonvisualfeedbacksimulationframework
AT xinzhao automatednumericalsimulationofbiologicalpatternformationbasedonvisualfeedbacksimulationframework
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