A Computational Framework for Bioimaging Simulation

Using bioimaging technology, biologists have attempted to identify and document analytical interpretations that underlie biological phenomena in biological cells. Theoretical biology aims at distilling those interpretations into knowledge in the mathematical form of biochemical reaction networks and...

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Main Authors:	Watabe, Masaki, Arjunan, Satya N. V., Fukushima, Seiya, Iwamoto, Kazunari, Kozuka, Jun, Matsuoka, Satomi, Shindo, Yuki, Ueda, Masahiro, Takahashi, Koichi
Format:	Online
Language:	English
Published:	Public Library of Science 2015
Online Access:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4509736/

id	pubmed-4509736
recordtype	oai_dc
spelling	pubmed-45097362015-07-24 A Computational Framework for Bioimaging Simulation Watabe, Masaki Arjunan, Satya N. V. Fukushima, Seiya Iwamoto, Kazunari Kozuka, Jun Matsuoka, Satomi Shindo, Yuki Ueda, Masahiro Takahashi, Koichi Research Article Using bioimaging technology, biologists have attempted to identify and document analytical interpretations that underlie biological phenomena in biological cells. Theoretical biology aims at distilling those interpretations into knowledge in the mathematical form of biochemical reaction networks and understanding how higher level functions emerge from the combined action of biomolecules. However, there still remain formidable challenges in bridging the gap between bioimaging and mathematical modeling. Generally, measurements using fluorescence microscopy systems are influenced by systematic effects that arise from stochastic nature of biological cells, the imaging apparatus, and optical physics. Such systematic effects are always present in all bioimaging systems and hinder quantitative comparison between the cell model and bioimages. Computational tools for such a comparison are still unavailable. Thus, in this work, we present a computational framework for handling the parameters of the cell models and the optical physics governing bioimaging systems. Simulation using this framework can generate digital images of cell simulation results after accounting for the systematic effects. We then demonstrate that such a framework enables comparison at the level of photon-counting units. Public Library of Science 2015-07-06 /pmc/articles/PMC4509736/ /pubmed/26147508 http://dx.doi.org/10.1371/journal.pone.0130089 Text en © 2015 Watabe et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
repository_type	Open Access Journal
institution_category	Foreign Institution
institution	US National Center for Biotechnology Information
building	NCBI PubMed
collection	Online Access
language	English
format	Online
author	Watabe, Masaki Arjunan, Satya N. V. Fukushima, Seiya Iwamoto, Kazunari Kozuka, Jun Matsuoka, Satomi Shindo, Yuki Ueda, Masahiro Takahashi, Koichi
spellingShingle	Watabe, Masaki Arjunan, Satya N. V. Fukushima, Seiya Iwamoto, Kazunari Kozuka, Jun Matsuoka, Satomi Shindo, Yuki Ueda, Masahiro Takahashi, Koichi A Computational Framework for Bioimaging Simulation
author_facet	Watabe, Masaki Arjunan, Satya N. V. Fukushima, Seiya Iwamoto, Kazunari Kozuka, Jun Matsuoka, Satomi Shindo, Yuki Ueda, Masahiro Takahashi, Koichi
author_sort	Watabe, Masaki
title	A Computational Framework for Bioimaging Simulation
title_short	A Computational Framework for Bioimaging Simulation
title_full	A Computational Framework for Bioimaging Simulation
title_fullStr	A Computational Framework for Bioimaging Simulation
title_full_unstemmed	A Computational Framework for Bioimaging Simulation
title_sort	computational framework for bioimaging simulation
description	Using bioimaging technology, biologists have attempted to identify and document analytical interpretations that underlie biological phenomena in biological cells. Theoretical biology aims at distilling those interpretations into knowledge in the mathematical form of biochemical reaction networks and understanding how higher level functions emerge from the combined action of biomolecules. However, there still remain formidable challenges in bridging the gap between bioimaging and mathematical modeling. Generally, measurements using fluorescence microscopy systems are influenced by systematic effects that arise from stochastic nature of biological cells, the imaging apparatus, and optical physics. Such systematic effects are always present in all bioimaging systems and hinder quantitative comparison between the cell model and bioimages. Computational tools for such a comparison are still unavailable. Thus, in this work, we present a computational framework for handling the parameters of the cell models and the optical physics governing bioimaging systems. Simulation using this framework can generate digital images of cell simulation results after accounting for the systematic effects. We then demonstrate that such a framework enables comparison at the level of photon-counting units.
publisher	Public Library of Science
publishDate	2015
url	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4509736/
_version_	1613250182336479232

A Computational Framework for Bioimaging Simulation

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